Author Archives: admin


Vitamin B12 is a limiting factor for induced cellular plasticity and … – Nature.com

Animal procedures

Animal experimentation at the IRB Barcelona was performed according to protocols approved by the Science Park of Barcelona (PCB) Ethics Committee for Research and Animal Welfare. Mice were housed in a specific pathogen-free facility on a 12-hour lightdark cycle at an ambient temperature of 2024C and humidity of 3070%. Adult mice were fed ad libitum with SAFE R40 pellet diet (https://safe-lab.com/safe_en/) containing 0.02mg per kg body weight vitamin B12. In general, mice of 816 weeks of age of both sexes were treated with 1mg ml1 doxycycline hyclate BioChemica (PanReac, A2951) in the drinking water (supplemented with 7.5% sucrose) for 7d. Antibiotic treatment was conducted using a broad-spectrum cocktail (1mg l1 each of ampicillin (BioChemica, A0839), neomycin sulfate and metronidazole (Sigma, M1547); 0.5mg l1 vancomycin (Cayman Chemical, CAY-15327) all dissolved in water supplemented with 7.5% sucrose) for 3 weeks before doxycycline initiation and was maintained during doxycycline treatment. Vitamin B12 (Sigma, V2876) supplementation was provided at 1.25mg l1 and folate supplementation was provided as folic acid (Sigma, F7876) at 40mg l1 in the drinking water, both for 7d concomitant with doxycycline treatment. For the B12 bolus experiment, mice were administered 5g vitamin B12 (Sigma, V2876) dissolved in water by oral gavage on day 6 after the start of doxycycline treatment, and blood samples were taken by submandibular collection just before and 24h after the bolus. OSKM transgenic mice are the i4F-B strain (derived on a C57/BL6J background and bred in house) described in ref. 3 and are available upon request. WT mice were i4F-B WT littermate controls where specified, or WT C57/BL6J (Charles River France).

Mice were treated with 2.5% (wt/vol) DSS, colitis grade (36,00050,000; MP Biomedicals, MFCD00081551) in drinking water for 5 consecutive days. On day 5, the DSS was removed and drinking water was supplemented with doxycycline hyclate BioChemica (1mg ml1; PanReac, A2951; with 7.5% sucrose) for 48h, after which regular water was returned. Mice in the B12 experimental group also received supplementation of vitamin B12 (1.25mg l1; Sigma, V2876) from the point of DSS removal (that is, day 5) until experimental endpoint. The MAT2Ai group received FIDAS-5 (MedChemExpres, HY-136144) and were dosed with 20mg per kg body weight per day dissolved in PEG400 by oral gavage as previously described79.

On day 9 (relative to the start of DSS administration), food was withdrawn from mice for 4h, after which mice were gavaged with FITCdextran (MW 4,000; Sigma-Aldrich, FD4) at a dose of 44mg per 100g of body weight dissolved in PBS. Food restriction was maintained for 3 additional hours, at which point blood was sampled by submandibular vein bleeding. Whole blood was diluted at a ratio of 1:4 in PBS, and 100l of blood/PBS mixture from each mouse was loaded into a 96-well plate. Fluorescence intensity was measured on a BioTek Synergy H1 Microplate Reader (excitation 490nm; emission 520nm).

Fresh stool samples were collected directly from mice and snap frozen. gDNA was isolated using a QIAamp DNA Stool Mini Kit (QIAGEN, 51504) according to the manufacturers protocols.

Libraries were prepared using the NEBNext Ultra DNA Library Prep Kit for Illumina (E7370L) according to the manufacturers protocol. Briefly, 50ng of DNA was fragmented to approximately 400bp and subjected to end repair plus A-tailing, ligation of NEB adaptor and Uracil excision by USER enzyme. Then, adaptor-ligated DNA was amplified for eight cycles by PCR using indexed primers. All purification steps were performed using AMPure XP Beads (A63881). Final libraries were analysed using an Agilent DNA 1000 chip to estimate the quantity and check size distribution, and were then quantified by qPCR using the KAPA Library Quantification Kit (KK4835, KapaBiosystems) before amplification with Illuminas cBot. Libraries were sequenced (2125bp) on Illuminas HiSeq 2500.

Reads were aligned to the mm10 genome using STAR 2.7.0a with default parameters80. DNA contaminated reads were filtered out from the analysis. The first and final ten bases of the non-contaminated reads were trimmed using DADA2 1.10.1 (ref. 81). Taxonomic assignments were carried out through Kaiju 1.7.0 (ref. 82) using the microbial subset of the NCBI BLAST non-redundant protein database (nr). Resulting sequencing counts were aggregated at genus level. Reads that could not be assigned to any specific genus were classified to the nearest known taxonomic rank (marked by the term _un). The gut microbial compositional plot displays the relative abundances (percentage) at genus level. Only the 17 most abundant taxa are shown, while the rest were moved to the others category. For all genera, the treatment effect (finish versus start) was compared between OSKM and control (WT) mice. This was accounted in a model with an interaction term (drug:treatment) using DESeq2 with default options83. The paired nature of the experimental design was taken into account in the model as an adjusting factor.

Decontamination from host and trimming was done following the same routines as for the taxonomic analysis. Cleaned sequences for all samples were assembled into contigs using megahit 1.2.4 (ref. 84), and prodigal 2.6.3 (ref. 85) was then used to predict the open reading frames inside the obtained contigs. Protein mapping and KEGG and COG annotations were obtained using the EggNOG mapper 2.0.0 (ref. 86). The abundance of the annotated genes was finally measured by counting aligned reads to them via Bowtie2, version 2.2.2, under default parameters87. Resulting counts data were aggregated at protein level. The treatment effect (finish versus start) was compared between OSKM and control (WT) mice. This was accounted in a model with an interaction term (drug:treatment) using DESeq2 with default options83. The paired nature of the experimental design was considered in the model as an adjusting factor. The top 500 protein hits from the fitted model (nondirectional set) as well as the top 200 positive hits and the top 200 negative hits (directional sets), in all cases ordered by statistical significance, were used to explore enrichment of functional annotations. In this regard, GO terms for bacteria and archaea were considered using the AmiGO 2 GO annotations database88, removing from the analysis gene sets with few genes (less than 8) and too many genes (more than 499). Statistically enriched GO terms were identified using the standard hypergeometric test. Significance was defined by the adjusted P value using the Benjamini and Hochberg multiple-testing correction. To take into consideration the compositional nature of the data, all DESeq2-based results were complemented with graphical representations of abundance log-ratio (between finish and start matched samples) rankings. This provides a scale invariant way (with regard to the total microbial load) to present the data89.

Blood was collected via submandibular vein bleed (D0, D2, D4) or intracardiac puncture following deep carbon dioxide anaesthetisation (D7) at approximately 12:0014:00h (46h into the light cycle) of each day. Whole blood was spun down for 10min at 3,381g at 4C and supernatant (serum) was separated and stored at 80C.

Acetonitrile (Sigma-Aldrich), isopropanol (Sigma-Aldrich), methanol (Sigma-Aldrich), chloroform (Sigma-Aldrich), acetic acid (Sigma-Aldrich), formic acid (Sigma-Aldrich), methoxyamine hydrochloride (Sigma-Aldrich), MSTFA (N-methyl-N-(trimethylsilyl) trifluoroacetamide; Sigma-Aldrich), pyridine (Sigma-Aldrich), 3-nitrophenylhydrazine (Sigma-Aldrich), N-(3-dimethylaminopropyl)-N-ethylcarbodiimide hydrochloride (EDC; Sigma-Aldrich) and sulfosalicylic acid (Sigma-Aldrich) as previously described90.

A volume of 25l of serum were mixed with 250l a cold solvent mixture with ISTD (methanol/water/chloroform, 9:1:1, 20C), into 1.5ml microtube, vortexed and centrifugated (10min at 15,000g, 4C). The upper phase of supernatant was split into three parts: 50l was used for gas chromatography coupled to mass spectrometry (GCMS) experiments in the injection vial, 30l was used for the short-chain fatty acid ultra-high performance liquid chromatography (UHPLC)MS method, and 50l was used for other UHPLCMS experiments.

The GCMS/MS method was performed on a 7890B gas chromatography system (Agilent Technologies) coupled to a triple-quadrupole 7000C (Agilent Technologies) equipped with a high-sensitivity electronic impact source (EI) operating in positive mode.

Targeted analysis was performed on an RRLC 1260 system (Agilent Technologies) coupled to a triple-quadrupole 6410 (Agilent Technologies) equipped with an electrospray source operating in positive mode. Gas temperature was set to 325C with a gas flow of 12l min1. Capillary voltage was set to 4.5kV.

Targeted analysis was performed on an RRLC 1260 system (Agilent Technologies) coupled to a triple-quadrupole 6410 (Agilent Technologies) equipped with an electrospray source operating in positive mode. The gas temperature was set to 350C with a gas flow of 12l min1. The capillary voltage was set to 3.5kV.

Targeted analysis was performed on an RRLC 1260 system (Agilent Technologies) coupled to a 6500+QTRAP (Sciex) equipped with an electrospray ion source.

The profiling experiment was performed with a Dionex Ultimate 3000 UHPLC system (Thermo Scientific) coupled to a Q-Exactive (Thermo Scientific) equipped with an electrospray source operating in both positive and negative mode and full scan mode from 100 to 1,200m/z. The Q-Exactive parameters were: sheath gas flow rate, 55 arbitrary units (a.u.); auxiliary gas flow rate, 15 a.u.; spray voltage, 3.3kV; capillary temperature, 300C; S-Lens RF level, 55V. The mass spectrometer was calibrated with sodium acetate solution dedicated to low mass calibration.

The peak areas (corrected to quality control) corresponding to each annotated metabolite identified in the serum of reprogrammable mice (n=6 per group) at day 5 and day 7 after doxycycline treatment were converted to log2 values. Data were represented as log2 fold change (log2 FC) values to each mouse at day 0 (before doxycycline administration). Metabolic pathway impact was calculated by Global ANOVA pathway enrichment and Out-degree Centrality Topology analysis through the MetaboAnalyst 4.0 software91, using KEGG library (2019) as a reference. The colour gradient from white to red indicates the P value, where red is most significant. Bubble size indicates the relative contribution of the detected metabolites in their respective KEGG pathway. Pathway impact scores the centrality of the detected metabolites in the pathway.

A total of 30l of mouse plasma was acidified with 3l solution of 15% phosphoric acid (vol/vol). Afterwards, 42l of methyl tert-butyl ether was added and vigorously mixed using a vortex. After 20min of reequilibration, samples were centrifuged for 10min at 21,130g at 4C. Next, 90l of acetonitrile were added to 10l of the aqueous phase to facilitate protein precipitation. After another cycle of centrifugation, the supernatant was transferred into a vial before LCMS analysis.

The extracts were analysed by a UHPLC system coupled to a 6490 triple-quadrupole mass spectrometer (QqQ, Agilent Technologies) with electrospray ion source (LCESIQqQ) working in positive mode. The injection volume was 3l. An ACQUITY UPLC BEH HILIC column (1.7m, 2.1150mm, Waters) and a gradient mobile phase consisting of water with 50mM ammonium acetate (phase A) and acetonitrile (phase B) were used for chromatographic separation. The gradient was as follows: isocratic for 2min at 98% B, from 2 to 9min decreased to 50% B, for 30s raised to 98%, and finally column equilibrated at 98% B until 13min. The flow rate was 0.4ml min1. The mass spectrometer parameters were as follows: drying and sheath gas temperatures, 270C and 400C, respectively; source and sheath gas flow rates, 15 and 11l min1, respectively; nebulizer flow, 35psi; capillary voltage, 3,000V; nozzle voltage, 1,000V; and iFunnel HRF and LRF, 130 and 100V, respectively. The QqQ worked in MRM mode using defined transitions. The transitions for doxycycline and the collision energy (CE(V)) were 445428(17), 44598(60).

In total, 25l of serum was mixed with 25l of TCEP and 70l of 1% formic acid in methanol. Samples were vortexed and left at 20C for 1h, centrifuged for 10min at 21,130g and 4C and transferred to glass vials for their analysis by LCMS.

LCMS was performed with a Thermo Scientific Vanquish Horizon UHPLC system interfaced with a Thermo Scientific Orbitrap ID-X Tribrid Mass Spectrometer.

Metabolites were separated by HILIC chromatography with an InfinityLab Poroshell 120 HILIC-Z 2.7m, 2.1mm100mm column (Agilent Technologies). The mobile phase A was 50mM ammonium acetate in water, and mobile phase B was acetonitrile. Separation was conducted under the following gradient: 02min, isocratic 90% B; 26min raised to 50% B; 67min, isocratic 50% B; 77.2min, increased to 90% B; 7.210.5min, reequilibration column 90% B. The flow rate was 0.4ml min1. The injection volume was 5l.

Samples were analysed in positive mode in targeted SIM mode and the following setting: isolation window (m/z), 4; spray voltage, 3,500V; sheath gas, 50 a.u.; auxiliary gas, 10 a.u.; ion transfer tube temperature, 300C; vaporizer temperature, 300C; Orbitrap resolution, 120,000; RF lens, 60%; AGC target, 2e5; maximum injection time, 200ms.

SAM (m/z 399.145) was monitored from 57min; Met (m/z 150.0583) from 3.25.2min; SAH (m/z 385.1289) from 46min; Hcy (m/z 136.0428) from 3.45.5min, as previously optimized using pure standards.

Approximately, 20mg of dry and pulverized stool samples were mixed with with 75l of TCEP and 210l of 1% formic acid in methanol. Samples were vortexed and subjected to three freezethaw cycles using liquid nitrogen. Subsequently, samples were left in ice for 1h, centrifuged for 10min at 21,130g and 4C and transferred to glass vials for their analysis by LCMS.

LCMS was performed with a Thermo Scientific Vanquish Horizon UHPLC system interfaced with a Thermo Scientific Orbitrap ID-X Tribrid Mass Spectrometer.

Metabolites were separated by HILIC chromatography with an InfinityLab Poroshell 120 HILIC-Z 2.7m, 2.1mm100mm column (Agilent Technologies). The mobile phase A was 50mM ammonium acetate in water, and mobile phase B was acetonitrile. Separation was conducted under the following gradient: 02min, isocratic 90% B; 26min raised to 50% B; 67min, isocratic 50% B; 77.2min, increased to 90% B; 7.210.5min, reequilibration column 90% B. The flow was 0.4ml min1. The injection volume was 5l.

Samples were analysed in positive mode in targeted SIM mode and the following setting: isolation window (m/z), 4; spray voltage, 3,500V; sheath gas, 50 a.u.; auxiliary gas, 10 a.u.; ion transfer tube temperature, 300C; vaporizer temperature, 300C; Orbitrap resolution, 120,000; RF lens, 60%; AGC target, 2e5; maximum injection time, 200ms. Cyanocobalamin was monitored from (m/z 1355.5747 and m/z 678.291) from 55.5min, as previously optimized using a pure standard.

Mouse serum was diluted at a 1:20 ratio in PBS and holotranscobalamin (holoTC) was measured using an ADVIA Centuar Immunoassay System (SIEMENS) with ADVIA Centuar Vitamin B12 Test Packs (07847260) according to the manufacturers instructions.

Cell pellets were mixed with 50l of TCEP and 140l of 1% formic acid in methanol (containing 150g l1 of Tryptophan-d5 as internal standard). Samples were vortexed and subjected to three freezethaw cycles using liquid nitrogen. Subsequently, samples were left at 20C for 1h, centrifuged for 10min at 21,130g and 4C and transferred to glass vials for their analysis by LCMS/MS.

Samples were analysed with an UHPLC 1290 Infinity II Series coupled to a QqQ/MS 6490 Series from Agilent Technologies (Agilent Technologies). The source parameters applied operating in positive electrospray ionization (ESI) were gas temperature: 270C; gas flow: 15l min1; nebulizer: 35psi; sheath gas heater, 400 a.u.; sheath gas flow, 11 a.u.; capillary, 3,000V; nozzle voltage: 1,000V.

The chromatographic separation was performed with an InfinityLab Poroshell 120 HILIC-Z 2.7m, 2.1mm100mm column (Agilent Technologies), starting with 90% B for 2min, 50% B from minute 2 to 6, and 90% B from minute 7 to 7.2. Mobile phase A was 50mM ammonium acetate in water, and mobile phase B was acetonitrile. The column temperature was set at 25C and the injection volume was 2l.

MRM transitions for SAM (RT: 6.1min) were 399298 (4V), 399250 (12V), 39997 (32V) and 399136 (24V) for M+0, and 400299 (4V), 400251 (12V), 40097 (32V), 400137 (24V), 400250 (12V) and 400136 (24V) for M+1.

Samples were fixed overnight at 4C with neutral buffered formalin (HT501128-4L, Sigma-Aldrich). Paraffin-embedded tissue sections (23m in thickness) were air-dried and further dried at 60C overnight for immunohistochemical staining.

Sections were stained with haematoxylin and eosin (H&E) for histological evaluation by a board-certified pathologist who was blinded to the experimental groups. Additionally, periodic acidSchiff staining (AR16592-2, Artisan, Dako, Agilent) was used to visualize mucus-producing cells on 34-m sections of colon that were counterstained with haematoxylin.

In the reprogramming model, the findings were evaluated by focusing mainly on the appearance of hyperplastic and dysplastic changes of the epithelial cells of the digestive mucosa and pancreatic acini. Inflammation and loss of the intestinal goblet cells were also reported. To document the severity and extension, a semi-quantitative grading system was used based on previously used histological criteria:

Gastric and colon mucosa inflammatory cell infiltrate and multifocal areas of crypt (large intestine) or glandular (stomach) epithelial cell dysplasia were scored from 0 to 5, where 0 indicates absence of lesion and 5 indicates very intense lesions.

Intestinal crypt hyperplasia: 1, slight; 2, twofold to threefold increase of the crypt length; 3, >threefold increase of the crypt length.

Goblet cell loss of the mucosa of the large intestine: 1, <10% loss; 2, 1050% loss; 3, >50% loss.

Histological total score was presented as a sum of all parameters scored for a given tissue.

In the colitis model, the following parameters were semi-quantitatively evaluated as previously described92 as follows:

Inflammation of the colon mucosa: 0, none; 1, slight, 2, moderate; 3, severe.

Depth of the injury: 0, none; 1, mucosa; 2, mucosa and submucosa; 3, transmural.

Crypt damage: 0, none; 1, basal and 1/3 damaged; 2, basal and 2/3 damaged; 3, only the surface epithelium intact; 4, entire crypt and epithelium lost.

Tissue involvement: 0, none; 1, 025%; 2, 2650%; 3, 5175%; 4, 76100%.

The score of each parameter was multiplied by the factor of tissue involvement and summed to obtain the total histological score.

Immunohistochemistry was performed using a Ventana discovery XT for NANOG and Sca1/Ly6A/E, the Leica BOND RX Research Advanced Staining System for H3K36me3, keratin 14 and vitamin B12, and manually for Ki67. Antigen retrieval for NANOG was performed with Cell Conditioning 1 buffer (950-124, Roche) and for Sca1/Ly6A/E with Protease 1 (5266688001, Roche) for 8min followed with the OmniMap anti-Rat HRP (760-4457, Roche) or OmniMap anti-Rb HRP (760-4311, Roche). Blocking was done with casein (760-219, Roche). Antigenantibody complexes were revealed with ChromoMap DAB Kit (760-159, Roche). For H3K36me3 and keratin 14, antigen retrieval was performed with BOND Epitope Retrieval 1 (AR9961, Leica) and for vit B12 with BOND Epitope Retrieval Solution 2 (Leica Biosystems, AR9640) for 20min, whereas for Ki67, sections were dewaxed as part of the antigen retrieval process using the low pH EnVision FLEX Target Retrieval Solutions (Dako) for 20min at 97C using a PT Link (Dako-Agilent). Blocking was performed with Peroxidase-Blocking Solution at room temperature (RT; S2023, Dako-Agilent) and 5% goat normal serum (16210064, Life technology) mixed with 2.5% BSA diluted in wash buffer for 10 and 60min at RT. Vitamin B12 also was blocked with Vector M.O.M. Blocking Reagent (MK-2213, Vector) following the manufacturers procedures for 60min. Primary antibodies were incubated for 30, 60 or 120min. The secondary antibody used was the BrightVision poly HRP-Anti-Rabbit IgG, incubated for 45min (DPVR-110HRP, ImmunoLogic) or the polyclonal goat Anti-Mouse at a dilution of 1:100 for 30min (Dako-Agilent, P0447). Antigenantibody complexes were revealed with 3-3-diaminobenzidine (K346811, Agilent or RE7230-CE, Leica). Sections were counterstained with haematoxylin (CS700, Dako-Agilent or RE7107-CE, Leica) and mounted with Mounting Medium, Toluene-Free (CS705, Dako-Agilent) using a Dako CoverStainer. Specificity of staining was confirmed by staining with a rat IgG (6-001-F, R&D Systems, Bio-Techne), a Rabbit IgG (ab27478, Abcam) or a mouse IgG1, kappa (Abcam, ab18443) isotype controls. See Supplementary Table 5 for primary antibody details.

Ready-to-use reagents from RNAscope 2.5 LS Reagent Kit-RED (322150, RNAScope, ACD Bio-Techne) were loaded onto the Leica Biosystems BOND RX Research Advanced Staining System according to the user manual (322100-USM). FFPE tissue sections were baked and deparaffinized on the instrument, followed by epitope retrieval (using Leica Epitope Retrieval Buffer 2 at 95C for 15min) and protease treatment (15min at 40C). Probe hybridization, signal amplification, colorimetric detection and counterstaining were subsequently performed following the manufacturers recommendations.

Hybridization was performed with the RNAscope LS 2.5 Probe - Mm-Lgr5 - Mus musculus leucine rich repeat containing G-protein-coupled receptor 5 (312178, RNAScope, ACD Bio-Techne). Control probe used was the RNAscope 2.5 LS Probe - Mm-UBC - Mus musculus ubiquitin C (Ubc), as a housekeeping gene (310778, RNAScope - ACD Bio-Techne). The bacterial probe RNAscope 2.5 LS Negative Control Probe_dapB was used as a negative control (312038, RNAScope - ACD Bio-Techne).

Brightfield images were acquired with a NanoZoomer-2.0 HT C9600 digital scanner (Hamamatsu) equipped with a 20 objective. All images were visualized with a gamma correction set at 1.8 in the image control panel of the NDP.view 2 U12388-01 software (Hamamatsu, Photonics).

Brightfield images of immunohistochemistry were quantified using QuPath software93 with standard detection methods. Where the percentage of tissue staining is calculated, pixels were classified as positive and negative using the Thresholder function. Where the percentage of cells is quantified, the Positive Cell Detection function was used.

MEFs were cultured in standard DMEM medium with 10% FBS (Gibco, LifeTechnologies, 10270106) with antibiotics (100U ml1 penicillinstreptomycin; Life Technologies, 11528876). Reprogramming of the doxycycline-inducible 4-Factor (i4F) MEFs with inducible expression of the four Yamanaka factors Oct4, Sox2, Klf4 and cMyc (OSKM) was performed as previously described3. Briefly, i4F MEFs were seeded at a density of 3105 cells per well in six-well tissue culture plates coated with gelatin and treated with doxycycline (PanReac, A2951) 1mg ml1 continuously to induce expression of the OSKM transcription factors in the presence of complete KSR media (15% (vol/vol) Knockout Serum Replacement (KSR, Invitrogen, 10828028) in DMEM with GlutaMax (Life Technologies, 31966047) basal media, with 1,000U ml1 LIF (Merck, 31966047), non-essential amino acids (Life Technologies, 11140035) and 100M beta-mercaptoethanol (Life Technologies, 31350010) plus antibiotics (penicillinstreptomycin, Gibco, 11528876)), which was replaced every 4872h. After 10d, iPS cell colonies were scored by alkaline phosphatase staining according to the manufacturers protocol (AP blue membrane substrate detection kit, Sigma, AB0300). Vitamin B12 (Sigma, V2876; 2M final), MAT2Ai PF-9366 (MedChemExpress, HY-107778; 2M final), SAM (S-(5-adenosyl)-l-methionine iodide, Merck, A4377; 100M final) and NSC636819 (Sigma-Aldrich, 5.31996; 10M final) were added continuously to the culture media and replaced every 4872h.

Reprogramming of WT MEFs was performed as previously described94. Briefly, HEK-293T (American Type Culture Collection, ATCC-CRL-3216) cells were cultured in DMEM supplemented with 10% FBS and antibiotics (penicillinstreptomycin, Gibco, 11528876). Around 5106 cells per 100-mm-diameter dish were transfected with the ecotropic packaging plasmid pCL-Eco (4g) together with one of the following retroviral constructs (4g): pMXs-Klf4, pMXs-Sox2, pMXs-Oct4 or pMXs-cMyc (obtained from Addgene) using Fugene-6 transfection reagent (Roche) according to the manufacturers protocol. The following day, media were changed and recipient WT MEFs to be reprogrammed were seeded (1.5105 cells per well of a six-well plate). Retroviral supernatants (10ml per plate/factor) were collected serially during the subsequent 48h, at 12-h intervals, each time adding fresh media to the 293T cells cells (10ml). After each collection, supernatant was filtered through a 0.45-m filter, and each well of MEFs received 0.5ml of each of the corresponding retroviral supernatants (amounting to 2ml total). Vitamin B12 supplementation (Sigma, V2876; 2M final concertation) began on the same day as viral transduction. This procedure was repeated every 12h for 2d (a total of four additions). After infection was completed, media were replaced by complete KSR media (see above). Cell pellets were harvested on day 5 (relative to the first infection) and histone extracts were processed for immunoblot as described below. On day 14 (relative to the first infection), iPS cell colonies were scored by alkaline phosphatase staining according to the manufacturers protocol (AP blue membrane substrate detection kit; Sigma, AB0300).

Doxycycline-inducible i4F MEFs were cultured as described in Cell culture above, with 1mg ml1 doxycycline, with without continuous vitamin B12 supplementation. At 72h after the addition of doxycycline, cells were transferred to complete KSR media containing a final concentration of 0.5mM l-Serine-13C3 (Sigma-Aldrich, 604887). This is the same concentration of unlabelled l-serine normally found in the complete KSR media, and was generated by ordering custom, serine-free DMEM (Life Technologies, ME22803L1) and custom, serine-free non-essential amino acid mixture (Life Technologies, ME22804L1). Six hours after the addition of labelled media, a subset of wells was harvested by scraping in PBS and centrifugation (300g for 5min); supernatant was removed and pellets were snap frozen. At 72h after the addition of the labelled media (that is, 6days into reprogramming), cells still in culture were transferred back to unlabelled complete KSR media, which was changed every 4872h. iPS cell colonies were analysed by alkaline phosphatase staining according to the manufacturers protocol (AP blue membrane substrate detection kit; Sigma, AB0300) on day 10. Doxycycline and vitamin B12 supplementation were continuous throughout the entire reprogramming protocol, and replenished with every media change (that is, every 4872h).

i4F MEFs were cultured in the presence doxycycline 2M of vitamin B12 over 3 or 10days (culture conditions as described above) and histone extracts were prepared using EpiQuik Total Histone Extraction Kit (EpiGentek, OP-0006-100) according to the manufacturers instructions. Around 200ng of total histone extract was used per well in the EpiQuik Histone H3 Modification Multiplex Assay Kit (Colorimetric; EpiGentek, P-3100) according to the manufacturers instructions.

Histone extracts were prepared using an EpiQuik Total Histone Extraction Kit (EpiGentek, OP-0006-100) according to the manufacturers instructions and quantified using DC Protein Assay Kit (Bio-Rad, 5000111). Whole-cell extracts were prepared in RIPA buffer (10mM Tris-HCl, pH 8.0; 1mM EDTA; 0.5mM EGTA; 1% Triton X-100; 0.1% sodium deoxycholate; 0.1% SDS; 140mM NaCl). A total of 10g of lysate was loaded per lane and hybridized using antibodies against H3K36me3, MS, vinculin, total histone H3 and LI-COR fluorescent secondary reagents (IRDye 800 CW anti-mouse, 926-32210; IRDye 680 CW anti-mouse, 926-68070; IRDye 800 CW anti-rabbit, 926-32211; IRDye 680 CW anti-mouse, 926-68071) all at a dilution of 1:10,000 according to manufacturers instructions. Immunoblots were visualized on an Odyssey FC Imaging System (LI-COR Biosciences). See Supplementary Table 5 for primary antibody details.

GSEAPreranked was used to perform a GSEA of annotations from MsigDB M13537, with standard GSEA and leading edge analysis settings. We used the RNA-seq gene list ranked by log2 fold change, selecting gene set as the permutation method with 1,000 permutations for KolmogorovSmirnoff correction for multiple testing95.

Genes belonging to the leading edge of the GSEA using the Met derivation signature (MsigDB, M13537) in the pancreas of reprogramming mice were selected. These genes were then compared to genes belonging to the leading edge of the same gene signature from i4F MEFs treated with doxycycline in vitro for 72h, as compared to OSKM MEFs treated with vitamin B12 (that is, genes in MsigDB M13537 whose upregulation was relieved by B12 supplementation in vitro). We selected 11 of these genes for which we had qPCR primers available.

Total RNA was extracted from MEFs with TRIzol (Invitrogen) according to the manufacturers instructions. Up to 5g of total RNA was reverse transcribed into cDNA using the iScript Advanced cDNA Synthesis Kit (Bio-Rad, 172-5038; pancreas) or iScript cDNA Synthesis Kit (Bio-Rad, 1708890; all other organs) for RTqPCR. Real-time qPCR was performed using GoTaq qPCR Master Mix (Promega, A6002) in a QuantStudio 6 Flex thermocycler (Applied Biosystem) or 7900HT Fast Real-Time PCR System (Thermo Fisher). See Supplementary Table 6 for primer sequences.

i4F MEFs were cultured in the presence or absence of doxycycline 2M of vitamin B12 (Merck, V2876) over 3days in six-well plates (culture conditions as described above). Cells were fixed with 1% (vol/vol) PFA (Fisher Scientific, 50980487) for 2min and then quenched with 750mM Tris (PanReac AppliChem, A2264) for 5min. Cells were washed twice with PBS, scraped, and spun down at 1,200g for 5min. Pellets were lysed with 100l (per well) lysis buffer (50mM HEPES-KOH pH 7.5, 140mM HCl, 1mM EDTA pH 8, 1% Triton X-100, 0.1% sodium deoxycholate, 0.1% SDS, protease inhibitor cocktail; Sigma, 4693159001) on ice for 10min, then sonicated using a Diagenode BioRuptor Pico (Diagenode, B01060010) for ten cycles (30s on, 30s off) at 4C. Lysates were clarified for 10min at 8,000g, 1% input samples were reserved, and supernatant was used for immunoprecipitation with Diagenode Protein A-coated Magnetic beads ChIPseq grade (Diagenode, C03010020-660) and H3K3me3 monoclonal antibody (Cell Signaling Technologies, 4909) with 0.1% BSA (Sigma, 10735094001). The following day, cells were washed once with each buffer: low salt (0.1% SDS, 1% Triton X-100, 2mM EDTA, 20mM Tris-HCl pH 8.0, 150mM NaCl), high salt (0.1% SDS, 1% Triton X-100, 2mM EDTA, 20mM Tris-HCl pH 8.0, 5,000mM NaCl), LiCl (0.25M LiCl, 1% NP-40, 1% sodium deoxycholate, 1mM EDTA, 10mM Tris-HCl pH 8.0) and eluted in 1% SDS, 100mM NaHCO3 buffer. Cross-links were reversed with RNase A (Thermo Fisher, EN0531), proteinase K (Merck, 3115879001) and sodium chloride (Sigma, 71376), and chromatin fragments were purified using QIAquick PCR purification kit (Qiagen, 28104).

i4F MEFs were cultured in the presence or absence of doxycycline and the indicated compounds over 3days in six-well plates (culture conditions as described above). After 72h, RNA was extracted using an RNeasy Kit (Qiagen, QIA74106) according to the manufacturers instructions.

The concentration of the DNA samples (inputs and immunoprecipitations) was quantified with a Qubit dsDNA HS kit, and fragment size distribution was assessed with the Bioanalyzer 2100 DNA HS assay (Agilent). Libraries for ChIPseq were prepared at the IRB Barcelona Functional Genomics Core Facility. Briefly, single-indexed DNA libraries were generated from 0.51.5ng of DNA samples using the NEBNext Ultra II DNA Library Prep kit for Illumina (New England Biolabs). Eleven cycles of PCR amplification were applied to all libraries.

The final libraries were quantified using the Qubit dsDNA HS assay (Invitrogen) and quality controlled with the Bioanalyzer 2100 DNA HS assay (Agilent). An equimolar pool was prepared with the 24 libraries and sequenced on a NextSeq 550 (Illumina). 78.9Gb of SE75 reads were produced from two high-output runs. A minimum of 23.97 million reads were obtained for all samples.

The concentration of total RNA extractions was quantified with the Nanodrop One (Thermo Fisher), and RNA integrity was assessed with the Bioanalyzer 2100 RNA Nano assay (Agilent). Libraries for RNA-seq were prepared at the IRB Barcelona Functional Genomics Core Facility. Briefly, mRNA was isolated from 1.5g of total RNA using the kit NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs). The isolated mRNA was used to generate dual-indexed cDNA libraries using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (New England Biolabs). Ten cycles of PCR amplification were applied to all libraries.

The final libraries were quantified using the Qubit dsDNA HS assay (Invitrogen) and quality controlled with the Bioanalyzer 2100 DNA HS assay (Agilent). An equimolar pool was prepared with the 12 libraries and submitted for sequencing at the Centre Nacional dAnlisi Genmica (CRG-CNAG). A final quality control by qPCR was performed by the sequencing provider before paired-end 50-nucleotide sequencing on a NovaSeq 6000 S2 (Illumina). Around 77.7Gb of PE50 reads were produced from three NovaSeq 6000 flow cells. A minimum of 55.7 million reads were obtained for all samples (Extended Data Fig. 7).

Total RNA extractions were quantified with a Nanodrop One (Thermo Fisher), and RNA integrity was assessed with the Bioanalyzer 2100 RNA Nano assay (Agilent). Libraries for RNA-seq were prepared at the IRB Barcelona Functional Genomics Core Facility. Briefly, mRNA was isolated from 1.2g of total RNA and used to generate dual-indexed cDNA libraries with the Illumina Stranded mRNA ligation kit (Illumina) and UD Indexes Set A (Illumina). Ten cycles of PCR amplification were applied to all libraries.

Sequencing-ready libraries were quantified using the Qubit dsDNA HS assay (Invitrogen) and quality controlled with the Tapestation HS D5000 assay (Agilent). An equimolar pool was prepared with the 15 libraries for SE75 sequencing on a NextSeq 550 (Illumina). Sequencing output was above 539 million 75-nucleotide single-end reads and a minimum of 28 million reads was obtained for all samples (Extended Data Fig. 7).

All analyses were performed in the R programming language (version 4.0.5)96 unless otherwise stated. Stranded paired-end reads were aligned to the Mus musculus reference genome version mm10 using STAR80 with default parameters. STAR indexes were built using the ENSEMBL annotation version GRC138.97. SAM files were converted to BAM and sorted using sambamba (version 0.6.7)97. Gene counts were obtained with the featureCounts function from the Rsubread package98 with the gtf file corresponding to ENSEMBL version GRC138.97 and parameters set to: isPairedEnd=TRUE and strandSpecific=2. Technical replicates were collapsed by adding the corresponding columns in the count matrix.

We obtained a reprogramming gene signature from published data48 and selected genes with false discovery rate (FDR) lower than 0.05 and fold change between MEF and d3-EFF larger than 2. The reprogramming score was defined as the average of all genes in the signature after scaling the rlog transformed matrix.

Exon counts were generated using the featureCounts function with parameters: isPairedEnd=TRUE, strandSpecific=2, GTF.featureType=exon, GTF.attrType=transcript_id, GTF.attrType.extra=gene_id, allowMultiOverlap=TRUE and useMetaFeatures=FALSE and the same GTF as for gene counts. Technical replicates were collapsed by adding the corresponding counts. For each gene, the longest annotated transcript was selected. Genes with less than four exons of RPKMs lower than exp(2) were discarded from the analysis. Intermediate exons were defined as those from the fourth to the penultimate. A total of 9,365 genes were used to compute the ratio between the intermediate and first exons. Fold changes between untreated and B12-treated samples were computed as the ratio between the exon ratios.

Genes were separated by their expression after transcript length and library size normalization (RPKM). For each sample, we computed the median ratios for genes in each decile.

Data were accessed from GSE131032. Reads were processed and ratios computed as previously described. log2 ratios for all transcripts were summarized through the median by sample. Comparisons between days were performed fitting a linear model to the medians using cage as a covariable. The function glht from the multcomp R package was used to find coefficients and P values.

To select genes most affected by the B12 treatment after reprogramming, we compared ratios between the doxy and MEF conditions and between the doxy and doxy+B12 conditions. Genes that increased the ratios in the first comparison (upper 25th percentile) and decreased the ratio in the second comparison (bottom 25%) were selected for functional enrichment analysis. A hypergeometric test was performed to find significant overlap between the defined gene set and the Biological Processes GO collection99.

Reads were aligned to the mm10 reference genome with bowtie100 version 0.12.9 with parameters --n 2 and --m 1 to keep reads with multiple alignments in one position. SAM files were converted to BAM and sorted using sambamba version 0.6.7.

For each sample, aligned reads were imported into R using the function scanBam from the Rsamtools package101. Whole-genome coverage was computed using the coverage function from the IRanges package102 and binned into 50-bp windows. Gene annotations were imported from Ensembl version GRCm38. The average coverage over gene bodies was computed using the normalizeToMatrix function from the EnrichedHeatmap package103 with parameters extend=1,000, mean_mode=w0 and w=50. Genes were filtered to coincide with those used in the exon ratio calculation from the RNA-seq data. Rows in the heat map were split by the average RNA-seq RPKM values in all samples.

BAM files were transformed to TDF files using the count function from IGVtools (version 2.12.2)104 with parameters --z 7, --w 25 and --e 250. Visualization of TDF files was generated using IGV (version 2.9.4)105.

Data were accessed from GSE109142. Reads were processed and ratios computed as previously described except using the ENSEMBL GRCm38.101 human gene annotation and the hg38 genome assembly version. The log2 ratios for all transcripts were summarized through the median by sample. Comparison between diagnosis status was performed fitting a linear model to the medians with sex and the expression quantiles as covariables. The model was fitted using the lm R function and coefficients and P values with the coeff function.

Unless otherwise specified, data are presented as the means.d. Statistical analysis was performed by Students t-test or one-way analysis of variance (ANOVA) as indicated, using GraphPad Prism v9.0.0, and specific statistical tests as indicated for each experiment for bioinformatic analyses. P values of less than 0.05 were considered as statistically significant. No statistical methods were used to predetermine sample size in the mouse studies, but our sample sizes are similar to those reported in previous publications3,9,16,17,19. Animals and data points were not excluded from analysis with the exception of the MEFs that failed to reprogram in the ChIP experiment, which is clearly detailed in the text. Mice were allocated at random to treatment groups, with attempts to balance initial body weight and sex as possible. The investigators were blinded during histological assessment of the mice; other data collection and analysis was not performed blind to the conditions of the experiments. Data distribution was assumed to be normal, but this was not formally tested. Figures were prepared using Illustrator CC 2019 (Adobe).

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

See the article here:
Vitamin B12 is a limiting factor for induced cellular plasticity and ... - Nature.com

Using patients’ own cells, researchers examine connection between … – ND Newswire

Although considered a rare disorder, fragile X syndrome is the most common genetic cause of intellectual disability in the world. Fragile X patients can have a range of mild to severe intellectual disability with the potential for other conditions such as autism, delayed motor development, hyperactivity, behavioral problems and seizures.

Although its well-known that fragile X is caused by the FMR1 gene, its less understood how the disorder physically affects brain development and function.

Christopher Patzke, the John M. and Mary Jo Boler Assistant Professor of Biological Sciences at the University of Notre Dame, is collaborating with fragile X patients and families to study the disorder.

My lab is hoping to find an explanation of the disease symptoms in humans, looking at the disorder at the cellular and molecular level, Patzke said.

By partnering with fragile X expert Dr. Elizabeth M. Berry-Kravis, professor of pediatrics at Rush University and a 1979 graduate of Notre Dame, the Patzke Lab has been able to collect patient tissue samples to create induced pluripotent stem cells. Because these stem cells mimic embryonic stem cells, the lab can then transform those cells into virtually any human cell the researchers want to study.

For this research, Patzke and his team are transforming pluripotent stem cells into brain cells that mimic neurons of someone with fragile X syndrome, creating a human model to study the genetic mutations effect on the brain.

Most of the genes associated with intellectual disability encode for proteins that do something with synapses, Patzke said. So making a cell culture of these fragile X neurons allows us, in a way, to zoom in to single cells and synapses, or the connections between neurons, and learn how these neurons communicate with one another.

The researchers then compare a patients cell culture sample to a corrected-cell culture sample, made via gene editing, to analyze the differences between how the synapses function with and without the FMR1 gene mutation.

Although research into fragile X syndrome is not uncommon, many researchers use animal models to study the FMR1 gene. While some of the research has led to clinical trials, those results have yet to translate into effective benefits for humans. By using tissue from fragile X patients, the goal is to overcome this gap in discovery.

In addition to fragile X syndrome, the Patzke Lab is also studying other disorders that cause intellectual disability including Down syndrome and Kabuki syndrome, another rare disorder.

Patzke is affiliated with Notre Dames Boler-Parseghian Center for Rare and Neglected Diseases, the first basic science rare disease research center in the nation. Focused on both basic and translational research, the center works with families affected by rare diseases to combine studies of patient data and tissue with fundamental biological research in order to better understand disease, identify molecular targets and develop new diagnostics and treatments.

Contact: Brandi Wampler, associate director of media relations, 574-631-2632, brandiwampler@nd.edu

Link:
Using patients' own cells, researchers examine connection between ... - ND Newswire

Seven Salk scientists named among best and most highly cited … – Salk Institute

November 15, 2023 November 15, 2023

LA JOLLASalk Professors Joseph Ecker, Ronald Evans, Satchidananda Panda, Rusty Gage, and Kay Tye, as well as Assistant Professor Jesse Dixon, have been named to the Highly Cited Researchers list by Clarivate. The 2023 list includes 6,849 researchers from 67 countries, all of whom demonstrate significant and broad influence reflected in their publication of multiple highly cited papers over the last decade. This is the ninth consecutive year that Ecker and Gage have made the list. Joseph Nery, a research assistant II in the Ecker lab, was also included on the list.

The Highly Cited Researchers list identifies and celebrates exceptional individual researchers at Salk, whose significant and broad influence in their fields translates to impact in their research community and innovations that make the world healthier, more sustainable, and more secure, says David Pendlebury, Head of Research Analysis at the Institute for Scientific Information at Clarivate. Their contributions resonate far beyond their individual achievements, strengthening the foundation of excellence and innovation in research.

Joseph Ecker Ecker is a professor in the Plant Molecular and Cellular Biology Laboratory, the director of the Genomic Analysis Laboratory, the Salk International Council Chair in Genetics, and a Howard Hughes Medical Institute investigator. His current research focuses on genomic and epigenomic regulation in plants and mammals and the application of DNA sequencing technologies for genome-wide analysis of DNA methylation, chromatin conformation, transcription, and gene function in single cells.

Ronald Evans Evans is a professor, the director of the Gene Expression Laboratory, and the March of Dimes Chair in Molecular and Developmental Biology. An expert in the essential roles of hormone receptors in reproduction, growth, and metabolism, Evans has identified novel pathways involved in cancer and metabolic diseases that are targetable by drugs that activate these receptors. More than a dozen approved drugs have been developed with Evans' technology for the treatment of leukemia, prostate cancer, breast cancer, liver disease, diabetes, and hypertension.

Satchidananda Panda Panda is a professor in the Regulatory Biology Laboratory and the director of the Wu Tsai Human Performance Alliance at Salk. He aims to understand how diet, exercise, and sleep affect cells and molecules in our body and to leverage this knowledge to elevate performance and reduce chronic diseases.

Rusty Gage Gage is a professor in the Laboratory of Genetics, the Vi and John Adler Chair for Research on Age-Related Neurodegenerative Disease, and the former president of the Salk Institute. He is a neuroscientist who studies the plasticity, adaptability, and diversity of the brain. By reprogramming human skin cells and other cells from patients with neurologic and psychiatric diseases into induced pluripotent stem cells, induced neurons, and organoids, his work is deciphering the progression and mechanisms that lead to disorders such as Alzheimer's disease, Parkinsons disease, bipolar disease, depression, and autism spectrum disorder.

Kay Tye Tye is a professor in the Systems Neurobiology Laboratory and the Wylie Vale Chair. She seeks to understand the neural-circuit basis of emotion that leads to motivated behaviors such as social interaction, reward-seeking, and avoidance. Her findings may help to inform treatments for a multitude of neuropsychiatric conditions such as anxiety, depression, addiction, and impairments in social behavior.

Jesse Dixon Dixon, a physician-scientist, is an assistant professor in the Gene Expression Laboratory and a member of the Salk Cancer Center faculty. He is a molecular biologist who uses molecular and computational approaches to explore how our genomes are organized in cells and how abnormal genome folding leads to human diseases such as cancer. His team is also developing new methods to study gene organization and gene function in single cells.

Joseph Nery Nery is a research assistant in the Ecker lab. He has been at the Salk Institute since 2006, where he specializes in epigenetics and runs computational analyses for the lab.

Here is the original post:
Seven Salk scientists named among best and most highly cited ... - Salk Institute

Perspectives of current understanding and therapeutics of Diamond … – Nature.com

Bartels M, Bierings M. How I manage children with Diamond-Blackfan anaemia. Br J Haematol. 2019;184:12333.

Article PubMed Google Scholar

Kang J, Brajanovski N, Chan KT, Xuan J, Pearson RB, Sanij E. Ribosomal proteins and human diseases: molecular mechanisms and targeted therapy. Signal Transduct Target Ther. 2021;6:323.

Article CAS PubMed PubMed Central Google Scholar

Dianzani I, Loreni F. Diamond-Blackfan anemia: a ribosomal puzzle. Haematologica. 2008 ;93:16014.

Article CAS PubMed Google Scholar

Ulirsch JC, Verboon JM, Kazerounian S, Guo MH, Yuan D, Ludwig LS, et al. The genetic landscape of Diamond-Blackfan anemia. Am J Hum Genet. 2018;103:93047.

Article CAS PubMed PubMed Central Google Scholar

Liu Y, Dahl M, Debnath S, Rothe M, Smith EM, Grahn THM, et al. Successful gene therapy of Diamond-Blackfan anemia in a mouse model and human CD34(+) cord blood hematopoietic stem cells using a clinically applicable lentiviral vector. Haematologica. 2022;107:44656.

Article CAS PubMed Google Scholar

Josephs HW. Anaemia of infancy and early childhood. Medicine. 1936;15:307451.

Article Google Scholar

Louis K, Diamond KB. Hypoplastic anemia. Am J Dis Child. 1938;56:4647.

Google Scholar

Gasser C. [Aplastic anemia (chronic erythroblastophthisis) and cortisone]. Schweiz Med Wochenschr. 1951;81:12412.

CAS PubMed Google Scholar

Allen DM, Diamond LK. Congenital (erythroid) hypoplastic anemia: cortisone treated. Am J Dis Child. 1961;102:41623.

Article CAS PubMed Google Scholar

August CS, King E, Githens JH, McIntosh K, Humbert JR, Greensheer A, et al. Establishment of erythropoiesis following bone marrow transplantation in a patient with congenital hypoplastic anemia (Diamond-Blackfan syndrome). Blood. 1976;48:4918.

Article CAS PubMed Google Scholar

Glader BE, Backer K, Diamond LK. Elevated erythrocyte adenosine deaminase activity in congenital hypoplastic anemia. N Engl J Med. 1983;309:148690.

Article CAS PubMed Google Scholar

Gustavsson P, Willing TN, van Haeringen A, Tchernia G, Dianzani I, Donner M, et al. Diamond-Blackfan anaemia: genetic homogeneity for a gene on chromosome 19q13 restricted to 1.8 Mb. Nat Genet. 1997;16:36871.

Article CAS PubMed Google Scholar

Gustavsson P, Skeppner G, Johansson B, Berg T, Gordon L, Kreuger A, et al. Diamond-Blackfan anaemia in a girl with a de novo balanced reciprocal X;19 translocation. J Med Genet. 1997;34:77982.

Article CAS PubMed PubMed Central Google Scholar

Draptchinskaia N, Gustavsson P, Andersson B, Pettersson M, Willig TN, Dianzani I, et al. The gene encoding ribosomal protein S19 is mutated in Diamond-Blackfan anaemia. Nat Genet. 1999;21:16975.

Article CAS PubMed Google Scholar

Gazda H, Lipton JM, Willig TN, Ball S, Niemeyer CM, Tchernia G, et al. Evidence for linkage of familial Diamond-Blackfan anemia to chromosome 8p23.3-p22 and for non-19q non-8p disease. Blood. 2001;97:214550.

Article CAS PubMed Google Scholar

Klar J, Khalfallah A, Arzoo PS, Gazda HT, Dahl N. Recurrent GATA1 mutations in Diamond-Blackfan anaemia. Br J Haematol. 2014;166:94951.

Article CAS PubMed Google Scholar

Sankaran VG, Ghazvinian R, Do R, Thiru P, Vergilio JA, Beggs AH, et al. Exome sequencing identifies GATA1 mutations resulting in Diamond-Blackfan anemia. J Clin Invest. 2012;122:243943.

Article CAS PubMed PubMed Central Google Scholar

Jaako P, Flygare J, Olsson K, Quere R, Ehinger M, Henson A, et al. Mice with ribosomal protein S19 deficiency develop bone marrow failure and symptoms like patients with Diamond-Blackfan anemia. Blood. 2011;118:608796.

Article CAS PubMed Google Scholar

Liu Y, Schmiderer L, Hjort M, Lang S, Bremborg T, Rydstrom A, et al. Engineered human Diamond-Blackfan anemia disease model confirms therapeutic effects of clinically applicable lentiviral vector at single-cell resolution. Haematologica. 2023;108:3095109.

Voit RA, Corey SJ. Gene therapy for congenital marrow failure syndromes - no longer grasping at straws? Haematologica. 2023;108:28802882.

Vlachos A, Muir E. How I treat Diamond-Blackfan anemia. Blood. 2010;116:371523.

Article CAS PubMed PubMed Central Google Scholar

Da Costa L, Leblanc T, Mohandas N. Diamond-Blackfan anemia. Blood. 2020;136:126273.

Article PubMed PubMed Central Google Scholar

Vlachos A, Ball S, Dahl N, Alter BP, Sheth S, Ramenghi U, et al. Diagnosing and treating Diamond Blackfan anaemia: results of an international clinical consensus conference. Br J Haematol. 2008;142:85976.

Article CAS PubMed PubMed Central Google Scholar

Faivre L, Meerpohl J, Da Costa L, Marie I, Nouvel C, Gnekow A, et al. High-risk pregnancies in Diamond-Blackfan anemia: a survey of 64 pregnancies from the French and German registries. Haematologica. 2006;91:5303.

PubMed Google Scholar

Flores Ballester E, Gil-Fernandez JJ, Vazquez Blanco M, Mesa JM, de Dios Garcia J, Tamayo AT, et al. Adult-onset Diamond-Blackfan anemia with a novel mutation in the exon 5 of RPL11: too late and too rare. Clin Case Rep. 2015;3:3925.

Article PubMed PubMed Central Google Scholar

Fargo JH, Kratz CP, Giri N, Savage SA, Wong C, Backer K, et al. Erythrocyte adenosine deaminase: diagnostic value for Diamond-Blackfan anaemia. Br J Haematol. 2013;160:54754.

Article CAS PubMed Google Scholar

Glader BE, Backer K. Elevated red cell adenosine deaminase activity: a marker of disordered erythropoiesis in Diamond-Blackfan anaemia and other haematologic diseases. Br J Haematol. 1988;68:1658.

Article CAS PubMed Google Scholar

Matsson H, Davey EJ, Draptchinskaia N, Hamaguchi I, Ooka A, Leveen P, et al. Targeted disruption of the ribosomal protein S19 gene is lethal prior to implantation. Mol Cell Biol. 2004;24:40327.

Article CAS PubMed PubMed Central Google Scholar

Amsterdam A, Sadler KC, Lai K, Farrington S, Bronson RT, Lees JA, et al. Many ribosomal protein genes are cancer genes in zebrafish. PLoS Biol. 2004;2:E139.

Article PubMed PubMed Central Google Scholar

Gianferante MD, Wlodarski MW, Atsidaftos E, Da Costa L, Delaporta P, Farrar JE, et al. Genotype-phenotype association and variant characterization in Diamond-Blackfan anemia caused by pathogenic variants in RPL35A. Haematologica. 2021;106:130310.

Article PubMed Google Scholar

Noel CB. Diamond-Blackfan anemia RPL35A: a case report. J Med Case Rep. 2019;13:185.

Article PubMed PubMed Central Google Scholar

Tamefusa K, Muraoka M, Washio K, Wakamatsu M, Shimada A. Late-onset familial Diamond-Blackfan anemia with neutropenia caused by RPL35A variant. Pediatr Int. 2022;64:e15275.

Article PubMed Google Scholar

Gazda HT, Sheen MR, Vlachos A, Choesmel V, ODonohue MF, Schneider H, et al. Ribosomal protein L5 and L11 mutations are associated with cleft palate and abnormal thumbs in Diamond-Blackfan anemia patients. Am J Hum Genet. 2008;83:76980.

Article CAS PubMed PubMed Central Google Scholar

Quarello P, Garelli E, Carando A, Cillario R, Brusco A, Giorgio E, et al. A 20-year long term experience of the Italian Diamond-Blackfan Anaemia Registry: RPS and RPL genes, different faces of the same disease? Br J Haematol. 2020;190:93104.

Article CAS PubMed Google Scholar

Ferreira R, Ohneda K, Yamamoto M, Philipsen S. GATA1 function, a paradigm for transcription factors in hematopoiesis. Mol Cell Biol. 2005;25:121527.

Article CAS PubMed PubMed Central Google Scholar

Ludwig LS, Gazda HT, Eng JC, Eichhorn SW, Thiru P, Ghazvinian R, et al. Altered translation of GATA1 in Diamond-Blackfan anemia. Nat Med. 2014;20:74853.

Article CAS PubMed PubMed Central Google Scholar

Gripp KW, Curry C, Olney AH, Sandoval C, Fisher J, Chong JX, et al. Diamond-Blackfan anemia with mandibulofacial dystostosis is heterogeneous, including the novel DBA genes TSR2 and RPS28. Am J Med Genet A. 2014;164A:22409.

Article PubMed Google Scholar

ODonohue MF, Da Costa L, Lezzerini M, Unal S, Joret C, Bartels M, et al. HEATR3 variants impair nuclear import of uL18 (RPL5) and drive Diamond-Blackfan anemia. Blood. 2022;139:311126.

Article PubMed PubMed Central Google Scholar

Yang YM, Karbstein K. The chaperone Tsr2 regulates Rps26 release and reincorporation from mature ribosomes to enable a reversible, ribosome-mediated response to stress. Sci Adv. 2022;8:eabl4386.

Article CAS PubMed PubMed Central Google Scholar

Kim AR, Ulirsch JC, Wilmes S, Unal E, Moraga I, Karakukcu M, et al. Functional selectivity in cytokine signaling revealed through a pathogenic EPO mutation. Cell. 2017;168:105364.e1015.

Article CAS PubMed PubMed Central Google Scholar

Szvetnik EA, Klemann C, Hainmann I, O Donohue M-F, Farkas T, Niewisch M, et al. Diamond-Blackfan anemia phenotype caused by deficiency of adenosine deaminase 2. Blood. 2017;130:874.

Mills EW, Green R. Ribosomopathies: theres strength in numbers. Science. 2017;358:eaan2755.

Liu Y, Deisenroth C, Zhang Y. RP-MDM2-p53 pathway: linking ribosomal biogenesis and tumor surveillance. Trends Cancer. 2016;2:191204.

Article PubMed PubMed Central Google Scholar

Hafner A, Bulyk ML, Jambhekar A, Lahav G. The multiple mechanisms that regulate p53 activity and cell fate. Nat Rev Mol Cell Biol. 2019;20:199210.

Article CAS PubMed Google Scholar

Zhang Y, Lu H. Signaling to p53: ribosomal proteins find their way. Cancer Cell. 2009;16:36977.

Article CAS PubMed PubMed Central Google Scholar

Danilova N, Sakamoto KM, Lin S. Ribosomal protein S19 deficiency in zebrafish leads to developmental abnormalities and defective erythropoiesis through activation of p53 protein family. Blood. 2008;112:522837.

Article CAS PubMed Google Scholar

Moniz H, Gastou M, Leblanc T, Hurtaud C, Cretien A, Lecluse Y, et al. Primary hematopoietic cells from DBA patients with mutations in RPL11 and RPS19 genes exhibit distinct erythroid phenotype in vitro. Cell Death Dis. 2012;3:e356.

Article CAS PubMed PubMed Central Google Scholar

Chakraborty A, Uechi T, Higa S, Torihara H, Kenmochi N. Loss of ribosomal protein L11 affects zebrafish embryonic development through a p53-dependent apoptotic response. PLoS One. 2009;4:e4152.

Article PubMed PubMed Central Google Scholar

Torihara H, Uechi T, Chakraborty A, Shinya M, Sakai N, Kenmochi N. Erythropoiesis failure due to RPS19 deficiency is independent of an activated Tp53 response in a zebrafish model of Diamond-Blackfan anaemia. Br J Haematol. 2011;152:64854.

Article CAS PubMed Google Scholar

Devlin EE, Dacosta L, Mohandas N, Elliott G, Bodine DM. A transgenic mouse model demonstrates a dominant negative effect of a point mutation in the RPS19 gene associated with Diamond-Blackfan anemia. Blood. 2010;116:282635.

Article CAS PubMed PubMed Central Google Scholar

McGowan KA, Li JZ, Park CY, Beaudry V, Tabor HK, Sabnis AJ, et al. Ribosomal mutations cause p53-mediated dark skin and pleiotropic effects. Nat Genet. 2008;40:96370.

Article CAS PubMed PubMed Central Google Scholar

Dutt S, Narla A, Lin K, Mullally A, Abayasekara N, Megerdichian C, et al. Haploinsufficiency for ribosomal protein genes causes selective activation of p53 in human erythroid progenitor cells. Blood. 2011;117:256776.

Article CAS PubMed PubMed Central Google Scholar

Here is the original post:
Perspectives of current understanding and therapeutics of Diamond ... - Nature.com

MetroHealth, Case Western Reserve University Cancer … – Newsroom MetroHealth

Dr. Wang Headshot

MetroHealth and Case Western Reserve University (CWRU) cancer researchers have solved a mystery surrounding a receptor protein that can suppress cancer or make it grow and spread. Their findings, detailing how and why the EphA2 receptor plays the roles of both cancer hero and villain, will be published in the journal Science November 16.

The team of researchers was led by Bingcheng Wang, PhD, Director of the MetroHealth Division of Cancer Biology and MetroHealth Research Institute Director of Basic Sciences.

Discoveries like this make it possible to treat cancer, said Dr. Wang, who also is the John A. and Josephine B. Wootton Endowed Chair of Research and professor at the Case Western Reserve School of Medicine and a member of the Case Comprehensive Cancer Center. As a cancer researcher, there is no greater accomplishment. Being asked to share this work with the scientific community through the prestigious journal Science is an honor. But the greatest reward is to know that we are making strides that will have a real impact on our own patients and others throughout world.

Dr. Wang, who has been studying the EphA2 receptor for 25 years, is recognized as a pioneer in the field. His lab has made several key discoveries around the receptor, which is overexpressed in solid tumors like prostate, breast, colon and lung cancers as well as the aggressive brain tumor glioblastoma.

In two landmark studies published in Nature Cell Biology in 2000 and 2001, Dr. Wangs lab was the first to make the groundbreaking discoveries that the EphA2 can suppress malignant behaviors of cancer cells. In 2009, his team reported in Cancer Cell that the same receptor also can have the opposite function after being modified by tumor-promoting proteins. The modified EphA2 causes cancer cells to proliferate, maintain stem cell properties and metastasize to other parts of the body.

Now, after years of investigation, the researchers have figured out how EphA2 plays these dual, opposing roles in cancer. Using a cutting-edge spectroscopic platform (PIE-FCCS) that allows molecular analysis on live cells, they saw that EphA2 is automatically assembled into small clusters on live cells through two different types of interactions among adjacent EphA2 molecules that glue them together. One interaction contributes to the hero role and the other triggers the villain side of the molecule.

The first author of the paper is Dr. Xiaojun (Roger) Shi, a postdoctoral scholar at the CWRU School of Medicine and a current trainee with the Cancer Biology Training Program of the National Cancer Institute. Roger made the discovery by combining his expertise in molecular imaging during doctoral thesis work and mastery of experimental cancer biology gained in the Wang lab.

As the lead contact author, Dr. Wang shares the findings in the Science article Time-Resolved Live Cell Spectroscopy Reveals EphA2 Multimeric Assembly. A large multidisciplinary team contributed to the work. Dimitar B. Nikolov, of Memorial Sloan Kettering Cancer Center, and Adam W. Smith, of Texas Tech University, are co-corresponding authors of the paper. Khalid Sossey-Alaoui, of MetroHealth and CWRU; Matthias Buck, of CWRU; Ben Brown and Jens Meiler, of Vanderbilt University; and Dolores Hambardzumyan, of Icahn School of Medicine at Mount Sinai, are among the co-authors who contributed to the work. The paper will be published online by the journal Science on Thursday, November 16.

As the inaugural Director of the Division of Cancer Biology in the Department of Medicine, Dr. Wang has played a significant role in MetroHealths strategic vision for research, successfully recruiting several nationally recognized cancer researchers. In 2021, he led the formation of a new Cancer Research Team, funded through millions of dollars in support and grants, to focus on ending the racial, ethnic, social and economic inequities that impact cancer diagnosis and treatment.

We know that many types of cancer disproportionately affect people of color, said MetroHealth President & CEO Airica Steed, Ed.D, RN, MBA, FACHE. This is why we are hyperfocused on eradicating health disparities and will continue to support the cutting-edge research that leads to these discoveries, so eventually all patients who face a diagnosis of cancer can hope for a long life, regardless of their cultural background, where they live or how much money they make.

John Chae, MD, MetroHealth Senior Vice President, Chief Academic Officer, said Dr. Wangs discoveries and other pivotal research being done at MetroHealth are reinforcing the Systems reputation as a world-class research institution.

This is the sort of foundational research that life-saving therapies are built upon, said Dr. Chae, who also is Senior Associate Dean for Medical Affairs at the CWRU School of Medicine. We are fortunate to have internationally respected researchers like Dr. Wang and the incredible team he has assembled. We will go on supporting this research and proving that some of the very best science in the world is being done in Cleveland at The MetroHealth System.

See more here:
MetroHealth, Case Western Reserve University Cancer ... - Newsroom MetroHealth

3D Cell Culture Market to grow by USD 1.28 billion from 2021 to … – PR Newswire

NEW YORK, Nov. 13, 2023 /PRNewswire/ -- The3D cell culture market size is expected to grow by USD 1.28 billion from 2021 to 2026. In addition, the momentum of the market will be progressing at a CAGR of15.69% during the forecast period, according to Technavio Research.The market is segmented by application (Cancer and stem cell research, Drug discovery and toxicology testing, and Tissue engineering and regenerative medicine) and geography (North America, Europe, Asia, and Rest of World (ROW)).The 3D cell culture market share growth by cancer and stem cell research segment will be significant during the forecast period.The rising prevalence of cancer and significant funding for cancer research are significant factors that are anticipated to drive the growth of the segment in focus during the forecast period.This report offers an up-to-date analysis of the current market scenario, the latest trends and drivers, and the overall market environment. Read FREE PDF Sample Report

Company Profile:

3D Biotek LLC, BICO Group AB, CN Bio Innovations Ltd., Corning Inc., Elveflow, Emulate Inc., Greiner Bio-One International GmbH, Hamilton Bonaduz AG, InSphero AG, Lonza Group Ltd., Merck KGaA, PromoCell GmbH, QGel SA, REPROCELL Inc., Synthecon Inc., SynVivoInc., Tecan Group Ltd., Thermo Fisher Scientific Inc., TissUse GmbH, and MIMETAS BV

3D Biotek LLC -The company offers 3D Cell Culture products such as 3D cell culture devices.

To gain access to more vendor profiles available withTechnavio, buy the report

Learn about the contribution of each segment summarized in conciseinfographics and thorough descriptions. View a FREE PDF Sample Report

3D Cell Culture Market: Geographical Analysis

North Americais estimated toaccount for41%of the global market duringthe forecast period. The primary markets for 3D cell culture in North America are the US and Canada. In this region, market growth is expected to outpace that in Europe and the Rest of the World (ROW). This accelerated growth can be attributed to substantial investments in new manufacturing facilities made by major companies like Becton, Dickinson, and Company, Corning Incorporated, and Thermo Fisher Scientific Inc. Such investments are set to drive the expansion of the 3D cell culture market in North America during the forecast period.

3D Cell Culture Market: Driver & Trend:

The increase in infectious diseases is notably driving the market growth.

Identify key trends, drivers, and challenges in the market. Download FREE sample to gain access to this information.

What are the key data covered in this 3D cell culture market report?

Related Reports:

The GlobalCell Culture Marketsize is estimated togrowat aCAGR of 11.3%between 2022 and 2027. The size of the market is forecasted to increase byUSD 17.74 billion.

The cell culture consumables market size is estimated togrowat a CAGR of 22.3%between 2022 and 2027. The size of the cell culture market is forecast to increase byUSD 23,729.7 million.

ToC:

Executive Summary

Market Landscape

Market Sizing

Historic Market Sizes

Five Forces Analysis

Market Segmentation by Application

Market Segmentation by Geography

Customer Landscape

Geographic Landscape

Drivers,Challenges, &Trends

Company Landscape

Company Analysis

Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provide actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.With over 500 specialized analysts, Technavio's report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio's comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research Jesse Maida Media & Marketing Executive US: +1 844 364 1100 UK: +44 203 893 3200 Email:[emailprotected] Website:www.technavio.com

SOURCE Technavio

See the rest here:
3D Cell Culture Market to grow by USD 1.28 billion from 2021 to ... - PR Newswire

Researchers chart the contents of human bone marrow – Science Daily

A team at Weill Cornell Medicine has mapped the location and spatial features of blood-forming cells within human bone marrow. Their findings confirm hypotheses about the anatomy of this tissue and provide a powerful new means to study diseases, ranging from noncancerous conditions, such as sickle cell anemia, to malignant conditions, such as acute leukemia, that affect bone marrow.

For the research described Sept. 29 in Blood, the investigators retrieved deidentified archival bone marrow samples from 29 patients at NewYork-Presbyterian/Weill Cornell Medical Center, generating a vast amount of data about the spatial relationships among their contents.

Creating images of bone marrow has been difficult historically, according to senior author Dr. Sanjay Patel, director of the Multiparametric In Situ Imaging (MISI) Laboratory in the Department of Pathology and Laboratory Medicine and an assistant professor of pathology and laboratory medicine at Weill Cornell Medicine. He and his colleagues overcame these challenges by devising a method for visualizing whole pieces of the tissue, then analyzing them with artificial intelligence (AI).

"We have been able to apply our approach to archival samples in a way that wasn't possible before," said Dr. Patel, who is also a hematopathologist at NewYork-Presbyterian/Weill Cornell Medical Center and a member of the Sandra and Edward Meyer Cancer Center at Weill Cornell Medicine. He noted that they succeeded in identifying and determining the positions of about 1.5 million cells in all.

Visualizing the Elusive Birthplace of Blood

Our blood cells get their start in the bone marrow, where stem cells produce the progenitors that in turn generate red and white blood cells, as well as the wound-sealing fragments known as platelets. Errors in these processes can give rise to acquired diseases including cancers, such as leukemia, lymphoma, and multiple myeloma, and those, such as sickle cell anemia, present from birth.

Studying the birth of blood cells within their native environment in human tissues, however, has proven challenging. What's more, when bone marrow samples are collected, the preservation technique can degrade some nucleic acids and proteins within the cells they contain. And, to avoid bias, researchers need to capture images of an entire piece of tissue, generating a daunting amount of data.

Dr. Patel's team came up with a series of solutions. They started by gathering samples from the tissue archive within Weill Cornell Medicine's Department of Pathology and Laboratory Medicine. These one-to-two-centimeter-long pieces of tissue came from patients who had received biopsies, but who had turned out to be disease free. Researchers in the MISI lab tested a variety of immune proteins known as antibodies, selecting from a catalog of thoroughly-vetted markers used in routine clinical diagnostics, to see which most effectively tagged the contents of bone marrow to make them visible with their fluorescence-based imaging instrumentation.

Their collaborators at BostonGene Corporation, a medical bioinformatics company, then used AI to analyze the resulting images, picking out individual cells, such as stem cells and the platelet-producing megakaryocytes, as well as bone, fat and blood vessels. This technology allowed the team to wrangle an otherwise unmanageable amount of information into a sophisticated analysis, according to Dr. Patel.

A New Way to Investigate Diseases

Previous studies have suggested that, during normal blood cell development, stem and progenitor cells inhabit certain locations, near bone and blood vessels, where surrounding cells create environments critical for their normal function. More recently, some research has suggested that these cells also gather around megakaryocytes, large cells that give rise to platelets. The team's analysis confirmed these patterns, including for megakaryocytes, in human samples. However, when they took patients' age into account, they found the cells were no longer as closely associated with megakaryocytes, which also tended to be smaller in older patients.

While these findings contribute to scientists' understanding of normal bone marrow, Dr. Patel sees the new method's greatest potential in investigating diseases, particularly along the course of their evolution. For a few conditions, such as acute myeloid leukemia, researchers already have evidence that the spatial arrangement of stem and progenitor cells may be disrupted. This new method could open the door to studies that specifically explore such changes -- and to those testing new treatments and evaluating existing ones, according to Dr. Patel.

"I hope our work unlocks the imagination of people who study diseases related to the bone marrow," he said.

Read the original:
Researchers chart the contents of human bone marrow - Science Daily

New study reveals the critical role of microglia in human brain … – EurekAlert

image:

Super-resolution image of human stem cell-derived Microglia cells with labeled mitochondria (yellow), nucleus (magenta), and actin filaments (cyan). These Microglia cells help in the maturation of neurons in human brain organoid models. Photo credit: A*STAR's SIgN

Credit: A*STAR's SIgN

An international team of scientists has uncovered the vital role of microglia, the immune cells in the brain that acts as its dedicated defense team, in early human brain development. By incorporating microglia into lab-grown brain organoids, scientists were able mimic the complex environment within the developing human brain to understand how microglia influence brain cell growth and development. This research represents a significant leap forward in the development of human brain organoids and has the potential to significantly impact our understanding of brain development and disorders. The study, iPS-cell-derived microglia promote brain organoid maturation via cholesterol transfer was published in Nature on 1 November 2023.

To investigate microglia's crucial role in early human brain development, scientists from A*STAR's Singapore Immunology Network (SIgN) led by Professor Florent Ginhoux, utilised cutting-edge technology to create brain-like structures called organoids, also known as mini-brains in the laboratory. These brain organoids closely resemble the development of the human brain. However, previous models were lacking in microglia, a key component of early brain development.

To bridge this gap, A*STAR researchers designed a unique protocol to introduce microglia-like cells generated from the same human stem cells used to create the brain organoids. These introduced cells not only behaved like real microglia but also influenced the development of other brain cells within the organoids.

A*STAR's Institute of Molecular and Cell Biology (IMCB)'s Dr Radoslaw Sobota and his team at the SingMass National Laboratory for Mass Spectrometry applied cutting edge quantitative proteomics approach to uncover changes in protein. Their analysis provided crucial insights into the protein composition of the organoids, further confirming the studys findings.

What sets this study apart is the discovery of a unique pathway through which microglia interact with other brain cells. The study found that microglia play a crucial role in regulating cholesterol levels in the brain.The microglia-like cells were found to contain lipid droplets containing cholesterol, which were released and taken up by other developing brain cells in the organoids. This cholesterol exchange was shown to significantly enhance the growth and development of these brain cells, especially their progenitors.

Cholesterol, makes up about 25% of the body's total cholesterol content, is abundantly present in the brain and is essential for the structure and function of neurons. Abnormal cholesterol metabolism has been linked to various neurological disorders, including Alzheimer's and Parkinson's Disease.

To investigate the roles of lipids in brain development and disease, researchers from the Department of Biochemistry at the Yong Loo Lin School of Medicine (NUS Medicine), led by Professor Markus Wenk, took on the crucial task of data acquisition, particularly in the field of lipidomics to draw valuable insights into the lipid composition and dynamics within the brain organoids containing microglia.

Using this information, another team from the Department of Microbiology and Immunology at NUS Medicine and led by Associate Professor Veronique Angeli, found that cholesterol affects the growth and development of young brain cells in human brain models. Microglia use a specific protein to release cholesterol, and when this process is blocked, it causes the organoid cells to grow more, leading to larger brain models. It has always been known that the microglia is key to brain development, however their precise role remains poorly understood. This finding from our team at the Department of Microbiology and Immunology is particularly impactful because we finally understand how cholesterol is transported. Our next focus will be finding out how we can regulate cholesterol release to optimise brain development and slow down, or prevent, the onset of neurological conditions, added Assoc Prof Veronique, who is also Director of the Immunology Translational Research Programme at NUS Medicine.

Moreover, Dr Olivier Cexus from the University of Surrey and formely at A*STAR, progressively deciphered the complex molecular interactions within the brain organoids using proteomic and lipidomic analysis. This provided valuable insights into the metabolic cross-talks involved in brain development and potential implications for diseases.

Together, these collective efforts were instrumental in deepening our understanding of the roles of microglia and the molecular components within brain organoids and its implications for human health.

Prof Florent Ginhoux, Senior Principal Investigator at A*STARs SIgN and Senior author of the study said, "Understanding the complex roles of microglia in brain development and function is an active area of research. Our findings not only advance our understanding of human brain development but also have the potential to impact our knowledge of brain disorders. This opens up new possibilities for future research into neurodevelopmental conditions and potential therapies."

Co-author of the study, Professor Jerry Chan, Senior Consultant, Department of Reproductive Medicine, KK Womens and Childrens Hospital, and Senior National Medical Research Council Clinician Scientist, added, There is currently a lack of tools to study how microglia interacts with the developing brain. This has hampered the understanding of microglia-associated diseases that play an important role during the early development of conditions such as autism, schizophrenia, and neurodegenerative diseases such as Alzheimers and Parkinsons disease.

The development of these novel microglia-associated brain organoids with same-donor pluripotent stem cells gives us an opportunity to study the complex interactions between microglia and neurons during early brain development. Consequentially, this may enable us to study the role of microglia in the setting of diseases and suggest ways to develop new therapies in time.

iPS-cell-derived microglia promote brain organoid maturation via cholesterol transfer

1-Nov-2023

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

Read the original post:
New study reveals the critical role of microglia in human brain ... - EurekAlert

Anti-aging molecule extends lifespan by improving cellular health – Earth.com

Researchers at the Buck Institute have made a significant breakthrough in the field of aging and disease with the discovery of a new drug-like molecule.

This molecule, known as MIC (Mitophagy-inducing compound), has been shown to extend lifespan and improve health in a variety of ways.

MIC operates by promoting healthy mitochondria through a process called mitophagy, which removes and recycles damaged mitochondria.

Mitochondria are crucial organelles in cells that produce energy, and their health is directly linked to overall cellular health and longevity.

The study demonstrated that this molecule extended the lifespan of C. elegans, a nematode worm frequently used in aging research.

MIC also improved mitochondrial function in mouse muscle cells and showed promise in ameliorating pathology in neurodegenerative disease models.

Mitochondrial dysfunction is known to play a role in various age-related diseases, including neurodegenerative disorders like Parkinsons and Alzheimers, cardiovascular diseases, metabolic disorders, muscle wasting, and cancer progression.

Despite the potential of treatments targeting mitochondrial dysfunction, none have been approved for human use to date.

The mitophagy-inducing compound is a coumarin, a type of naturally bioactive compound found in many plants and certain types of cinnamon.

Coumarins are known for their diverse health benefits, including anticoagulant, antibacterial, antifungal, antiviral, anticancer, antihyperglycemic properties, and neuroprotective effects.

The discovery of the effects of MIC originated from a study on Parkinsons disease. A team of experts including Dr. Julie Andersen and Dr. Shankar Chinta were examining known enhancers of mitophagy in a mouse model.

The mitophagy-inducing compound emerged as a significant find in their research. Instead of immediately testing MIC in mice, the researchers opted to study its impact on overall aging and its mechanism of action using the C. elegans model.

This approach led to the discovery that MIC belongs to a different class of molecules that enhance the expression of a key protein in autophagy and lysosomal functions (TFEB).

The study, led by Dr. Andersen and research scientist Dr. Manish Chamoli, revealed that MIC activates the transcription factor TFEB, a master regulator of genes involved in autophagy and lysosomal functions. Autophagy is an intracellular recycling process vital for cellular health.

The research findings are significant as they show MICs potential in not only extending lifespan but also preventing mitochondrial dysfunction in mammalian cells, offering new avenues for treating various age-related diseases.

Theres a bottleneck in efforts to develop potential therapeutics in the field of geroscience, and the bottleneck is that we dont have enough molecules in the pipeline, said study senior co-author Dr. Gordon Lithgow.

MIC is a great candidate to bring forward given its therapeutic effect across multiple models and the fact that it is a naturally occurring molecule.

Anti-aging strategies encompass a variety of practices and research areas focused on slowing down or reversing the aging process. Here are some key areas:

This includes a balanced diet rich in antioxidants, regular physical activity, adequate sleep, and stress management. Avoiding smoking and excessive alcohol consumption also plays a critical role.

Using sunscreen to protect the skin from UV damage, along with regular use of moisturizers and anti-aging products like retinoids and peptides, can help maintain skin health.

These include hormone replacement therapies, cosmetic procedures like Botox or fillers, and plastic surgery. These methods should be approached cautiously and under medical supervision.

Some people use supplements like omega-3 fatty acids, vitamin D, coenzyme Q10, and others believed to have anti-aging effects. However, their effectiveness can vary and should be used judiciously.

Areas like telomere therapy, stem cell research, and gene editing are being explored for potential anti-aging benefits. While promising, many of these are still in the experimental stages.

Maintaining mental health and active social life is essential. Activities that stimulate the mind, like puzzles, reading, and learning new skills, along with regular social interaction, can contribute to longevity and quality of life.

Regular visits to healthcare professionals for check-ups can help in early detection and management of age-related diseases.

Certain foods are known for their potential anti-aging benefits, mainly due to their high antioxidant content and other beneficial nutrients. Heres a list of some of these foods:

Incorporating these foods into a balanced diet can contribute to overall health and potentially slow some aspects of the aging process. Its also important to maintain a diverse diet and consult with a healthcare professional, especially when making significant dietary changes.

The research is published in the journal Nature Aging.

Like what you read? Subscribe to our newsletter for engaging articles, exclusive content, and the latest updates.

-

Check us out on EarthSnap, a free app brought to you by Eric Ralls and Earth.com.

Continue reading here:
Anti-aging molecule extends lifespan by improving cellular health - Earth.com

Pancreas gene finding gives new insights into human development … – EurekAlert

Understanding how the human pancreas develops is crucial to allow scientists to make insulin producingbeta cells in the quest to cure Type 1 diabetes. Now, scientists have made a unique and surprising discovery - a gene that is essential for making the pancreas in humans is not present in almost all other animals.

Beta cells within the pancreas produce insulin that regulate blood sugar. Every mammal needs the pancreatic beta-cells to survive. In established Type 1 diabetes there are no, or very few, working beta-cells.

The new finding, published in Nature Genetics, challenges assumptions about how the regulation of development evolves. Until now, scientists had assumed that genes essential for development of key organs and functions were highly conserved through evolution, meaning the genetic pathway remains the same between different species, from fish to humans. However, the gene, called ZNF808, is only found in humans, other apes such as chimpanzees and gorillas, and in some monkeys, such as macaques.

This Wellcome Trust-funded research was carried out by researchers at the University of Exeter Medical School, the University of Cambridge and the University of Helsinki in Finland. The study shows just how different humans can be to other animals often used in research, such as mice, emphasising the importance of studying the human pancreas.

Lead author Dr Elisa De Franco, of the University of Exeter Medical School, said: Our finding is really surprising this is the only example we know of where a gene that is fundamental to the development of an organ in humans and primates is not present in other animals. Youd expect a gene only found in primates to regulate a feature that is specific to primates, such as brain size, but it is not the case for this gene, which instead is involved in development of an organ shared by all vertebrates! We think this shows that there must have been an evolutionary shift in higher primates to serve a purpose.

Senior author Professor Andrew Hattersley, of the University of Exeter Medical School, said: One hypothesis that we are exploring is that the evolutionary benefit is to the pancreas in the fetus. Human babies are born through the pelvis, so they cannot stay in the uterus for a longtime as they would grow too large for birth. Instead to cope with being born early and needing to survive without continual feeding they need to be born with more fat than any other animal. This fat is laid down when the fetus pancreas produces more insulin. Our research has shown that human fetuses have more insulin-related growth than other animals.

Dr Nick Owens, of the University of Exeter Medical School, remarked This research really emphasises the importance of studying the human pancreas in order to understand and find new treatments for diabetes. Animal research is important, but it can only tell us so much. We know there are fundamental differences between humans and other animals, such as mice which are often the subject of research in this field. The human pancreas is different in how it looks, works and develops. Our genetic finding could help us understand why thats the case.

ZNF808 belongs to a family of recently evolved proteins which bind and switch off specific regions of the DNA which have also developed recently in evolutionary terms. These DNA regions were among the regions considered junk DNA with no meaningful purpose for decades, but new technology have recently allowed us to discover their functions. Our findings confirm that these regions of our DNA are playing important roles during human development.

Dr Michael Imbeault, from the University of Cambridge, said These findings show that genes like ZNF808, even if relatively recent in evolution, can have a crucial role in human development. ZNF808 is a member of the largest, but also least studied family of proteins that regulate our genome. There are hundreds of genes like ZNF808 in our DNA, many primate or even human specific, and our results demonstrate how these can be key players in human health..

The identification of ZNF808 as being involved in human pancreas development occurred after researchers at the University of Exeter examined genetic samples from patients recruited across the world who were born without a pancreas and found that they all had genetic changes resulting in loss of ZNF808. They then teamed up with colleagues at the University of Cambridge and Helsinki University to study the effect of ZNF808 loss using stem cells in the lab. The results showed that ZNF808 plays an important function early during human development when cells need to decide whether to become pancreas or liver.

Among those who shared their genetic samples was Tania Bashir, aged 12, from Luton. Her father Imran Bashir welcomed the Exeter teams progress. Having an answer to why this happened is important. Weve always wanted to know now we do. The next important step is to understand what this means to the future of science. My dream is that one day, scientists will be able to genetically modify a stem cell and grow a human pancreas, and implant that into Tania, and potentially cure her. I dont know if that will ever be possible, but I do know that this understanding is a crucial step forward.

Professor Timo Otonkoski from University of Helsinki remarked The input of people born without a pancreas was fundamental to this discovery. Nobody would have ever thought that ZNF808 played a role in pancreatic development if we hadnt found the changes in this gene in these patients. The ultimate goal of our research is for this knowledge to be translated into being able to manipulate stem cells to produce beta cells that can produce insulin in the laboratory. That could be the key to curing type 1 diabetes. Our finding is a significant step in understanding what makes the human pancreas unique, which could help progress this area.

The research was supported by the Wellcome Trust, Diabetes UK, and by the Exeter NIHR Biomedical Research Centre. The paper is entitled Primate-specific ZNF808 is essential for pancreatic development in humans and is published in Nature Genetics.

Tanias story

Tania Bashir, Twin 2, weighed just 1.1kg when she was born, via emergency caesarean section, five weeks premature, without a pancreas.

Her mother Saiqa said: From week 20 onwards the weekly scans were stressful. We were told there was a high chance that the smaller twin wouldnt make it, so we kept the fact we had a twin a secret from friends, family and even her other three siblings.

Tanias father Imran, a chartered hardware engineer in Luton, recalled: Tania weighed about as much as a bag of sugar; you could quite easily fit her in the palm of your hand They immediately realised she had neonatal diabetes, but she was also not growing or gaining weight. It took eight weeks of investigations, tests and scans to figure out she had no pancreas. Our lives have never been the same since.

As well as producing no insulin to control her blood sugar, Tania, now 12, does not produce the enzymes that break down fats, proteins and carbohydrates into smaller molecules such as triglycerides, amino acids, and sugars so they can pass through the intestine into the bloodstream. Today, with the support of her parents, she lives a relatively normal life, despite still needing a special liquid feed via a tube at night and permanently using an insulin pump. But her dad recalls the dark days of fear and uncertainty when she was small.

First, we were told she wouldnt survive till birth, then that she wouldnt survive the next few weeks I remember consciously thinking that I didnt want to get too attached, because one of us would have to be strong when she died. In the end, we stopped asking. You normally look to the medical professionals for answers, but because the condition was so rare, there just is not the experience in the UK or across the world. We were learning along with the medical professionals, pushing each other to find better solutions for Tania. We are really lucky to have a fantastic team at the Luton and Dunstable hospital.

Imran found a small network of families globally via Facebook, which provided some shared experience. When Tania was six months old, the family was connected to the research team at the University of Exeter, who specialise in genetic causes of diabetes. They visited the lab and Imran said: I remember thinking, I like what theyre trying to do here we could get an answer.

A decade later, through sequencing all the genes in Tanias DNA (a technique called whole exome sequencing) the Exeter team has identified a gene which is crucial to the development of the human pancreas and is only present in humans and some monkeys, but not in other mammals. Tanias genetic sample was one of just 13 of children born without a pancreas to enable this discovery.

Imran welcomed the progress. Having an answer is important. It draws a line under the question of why, but the journey is far from over. Unlike people with type 1 diabetes, Tanias immune system didnt attack her pancreas so a pancreas could function in her body. I believe that it might be possible to use this research to modify stem cells and grow a pancreas using Tanias own cells, which could be implanted into her. I know it sounds like science fiction, but 40 years ago, there was no such thing as the internet. Now we can share moments instantly across the world. Theres some amazing scientific progress going on in the world, and the work done by Exeter has brought us one step closer to making my dream possible.

Dr Elisa de Franco, of the University of Exeter Medical School, said: Our findings really show the importance of studying the DNA of people with rare diseases to understand how organs develop and function. We are immensely grateful to people like Tania and her family, without them none of this would be possible.

Case study

People

Primate-specific ZNF808 is essential for pancreatic development in humans

Here is the original post:
Pancreas gene finding gives new insights into human development ... - EurekAlert