Stem Cell Clinic

Single-cell analysis reveals different age-related somatic mutation profiles between stem and differentiated cells in human liver – Science Advances

INTRODUCTION

Genome integrity is critically important for cellular function. Evidence has accumulated that loss of genome integrity and the increasingly frequent appearance of various forms of genome instability, from chromosomal aneuploidy to base substitution mutations, are hallmarks of aging (1, 2). However, thus far, of all mutation types, only chromosomal alterations could readily be studied directly during in vivo aging using cytogenetic methods (3). Because of their small size, random nature, and low abundance, most somatic mutations are difficult to detect, except in single cells or in clonal lineages (4). In the past, using transgenic reporters, mutations have been found to accumulate with age in a tissue-specific manner (5). However, this approach does not allow a genome-wide, direct analysis of somatic mutations in human primary cells. More recently, using single-cell whole-genome sequencing (WGS), somatic mutations were found to accumulate with age in human neurons (6) and B lymphocytes (7). Others also reported increased somatic mutations in human primary cells isolated from intestine, colon, and liver, albeit in clones propagated from human tissue-specific stem cells (8), which may not be representative of the differentiated cells that ultimately provide tissue function. Nevertheless, together, these studies confirmed that mutations in different somatic cell types of humans accumulate with age.

Here, we present single-cell genome-wide somatic mutation profiles of differentiated human liver hepatocytes as compared with adult liver stem cells (LSCs). Human liver is of particular interest for studying genome instability because of its high metabolic activity and its role in detoxification of xenobiotics, which makes this organ the most important target for genotoxicity in the body. In humans, accumulation of de novo mutations could contribute to the observed age-related loss of liver function, most notably a severe reduction in metabolic capacity, and multiple pathologies, including fatty liver disease, cirrhosis, hepatitis, infections, and cancer (9, 10). Our results indicate high spontaneous mutation frequencies in differentiated hepatocytes that significantly increase with age. By contrast, mutation frequencies in adult LSCs, defined as the cells that give rise to clonal outgrowths, were fairly low. In differentiated hepatocytes, a considerable number of mutations were found in functional parts of the genome. These results indicate that the human liver is subject to a high burden of genotoxicity and that adult stem cells are a critical component in maintaining overall genome integrity within a tissue.

The quantitative detection of de novo somatic mutations in single cells after whole-genome amplification (WGA) and WGS remains a challenge because of the high chance of errors. Here, we used a well-validated, highly accurate method, single-cell multiple displacement amplification (single-cell MDA, or SCMDA) (11), to analyze somatic mutations in single primary hepatocytes from human donors varying in age between 5 months and 77 years. These cells were isolated shortly after death through perfusion of whole livers from healthy human individuals after informed consent by the donors family (Lonza Walkersville Inc.). Cell viability was higher than 80% and, after Hoechst staining, individual, diploid hepatocytes were isolated via fluorescence-activated cell sorting (FACS) into individual polymerase chain reaction (PCR) tubes (fig. S1A). In total, we sequenced four single hepatocytes and bulk genomic liver DNA for each of 12 human donors (table S1). Each cell was subjected to our recently developed procedure for WGA and WGS (11, 12). Somatic single-nucleotide variants (SNVs) in single cells were identified relative to bulk genomic DNAs at a depth of 20 using VarScan2, MuTect2, and HaplotypeCaller with certain modifications (Materials and Methods and table S2). Overlapping mutations from this tricaller procedure were exclusively considered for further analysis. The results were essentially confirmed by using two alternative variant callers: SCcaller (11) and LiRA (Linked Read Analysis) (13).

After adjusting for genomic coverage, the number of SNVs per cell for 48 hepatocytes from 12 donors was found to vary between 357 and 5206 with four extreme outliers of 20,557 to 37,897 SNVs per cell excluded from the statistical model (Fig. 1A and table S2). The number of mutations per cell was found to increase significantly with the age of the donor (P = 1.22 109), with median values of 1222 855 SNVs per cell in the young group (36 years, n = 21 cells), and 4054 1168 SNVs per cell in the aged group (46 years, n = 23 cells), excluding the four outliers (Fig. 1A). The median number of mutations per cell in hepatocytes from the youngest donor was in the same range as what we recently reported for primary human fibroblasts from young donors, i.e., 1027 and 926 SNVs per cell from the 5-month-old and 6-year-old donors, respectively (11, 12). However, during aging, mutation levels increased over the same age range up to 2.5 times higher than in our previously analyzed human B lymphocytes (7) or human neurons analyzed by others (6) (fig. S2A).

(A) SNV levels in individual differentiated hepatocytes. The y axis on the left indicates the number of mutations per cell, and the y axis on the right indicates mutation frequency per base pair. The median values with SDs among four cells of each subject are indicated. Data indicate an exponential increase in mutation frequency with donor age (R = 0.892, P = 1.16 106). bp, base pair. (B) SNV levels in LSC-derived parent clones (red) and their kindred cells (light green) from three young donors. The Venn diagrams indicate the fraction of SNVs detected in the parent clones (collectively for each individual; n = 3) that were also detected in the kindred LSCs. The bars indicate the median mutation frequencies in clones (red) and kindred single cells (light green). (C) Comparison of SNV levels in differentiated hepatocytes (dark green dots; n = 24 from six donors) and LSCs (light green; n = 10 from three donors), all within the young donor group 36 years. Mutation frequencies were corrected for the estimated number of cell divisions. (D) SNV levels in LSCs and differentiated hepatocytes from the same participants, corrected for the estimated number of cell divisions.

At this stage, we were interested in the possible cause of the high mutation frequencies in the four outlier cells. Three of the four outliers with the highest SNV levels revealed multiple mutations in genes involved in DNA repair (table S3) (14), which could conceivably underlie the observed accelerated mutation accumulation in these cells. Of note, individual outlier cells with high mutation levels have been detected in other tissues (6, 7).

Together, these findings indicate that the liver is prone to high levels of de novo somatic mutations, which could possibly be related to its major role in the metabolization and detoxification of xenobiotics.

The mutation frequencies observed in human hepatocytes from older subjects were higher than those previously found in human neurons and B lymphocytes (6, 7). They were also higher than the mutation frequencies reported for stem cellderived liver organoids (fig. S2B) (8). It is critically important to validate the results obtained with single-cell mutation analysis to rule out possible amplification artifacts. In our previous studies on human primary fibroblasts, we validated single-cell data by also analyzing unamplified DNA from clones derived from cells in the same population (11). Here, we generated liver-specific clones from young donors by plating the prepurified hepatocyte cell suspensions in selective medium for LSC expansion (Materials and Methods). Under these conditions, the differentiated hepatocytes died within 5 to 7 days, while the residential LSCs could be propagated without differentiation. The latter was confirmed using biomarker analysis (Materials and Methods and fig. S1B) (15, 16). In addition, we obtained from a commercial source one sample of human postnatal LSCs from a 1-year-old donor at passage 9 (approximately 27 population doublings), which were expanded and also grown into clones in the same way.

LSC clones could be established only from young individuals, i.e., hepatocyte samples from the 1-year-old, 5-month-old, and 18-year-old participants. This is in keeping with observations that resident stem cell properties change with age, with a general reduction in proliferative capacity and increased cellular senescence (17).

Both LSC clones and kindred single cells derived from the young individuals were processed and subjected to WGS, as described above for differentiated hepatocytes. We then tested for the fraction of mutations called in the clones that were also found in the single cells derived from them. As shown in the Venn diagrams (Fig. 1B and fig. S3, A and B), most of these mutations were indeed confirmed in the single cells. This is very similar to what we previously reported for human single fibroblasts and clones derived from the same population of cells (11), which underscores the validity of our single-cell mutation detection method, also in liver cells. Of note, most of the mutations found in the single cells, but not in their parental clones, are likely to be also real. These are likely either mutations missed during variant calling in the clone or de novo mutations arising in the individual cells during clone culture and expansion.

Once we confirmed the validity of our single-cell data, we directly compared mutation frequencies between the single cells defined as LSCs and differentiated hepatocytes, both from the young donor group. Previous studies have provided evidence for lower spontaneous mutation frequencies in stem as compared with differentiated cells (18, 19). For this comparison to be valid, we compared mutation frequencies per cell division in both cell types. This was necessary because the number of cell divisions is a major factor in causing base substitution mutations through replication errors. We first estimated the number of cell divisions that had occurred in human somatic cells of the young age group since the zygote, as described previously (20) (Materials and Methods). We then added, only to the LSCs, the estimated additional numbers of cell divisions during culture (Materials and Methods). The results show that, on a per cell division basis, somatic mutation frequencies were indeed lower in the LSCs than in the differentiated hepatocytes (about twofold), i.e., 11 SNVs versus 21 SNVs per cell per mitosis, respectively (P = 1.26 104, two-tailed Students t test) (Fig. 1C and table S2). A reduced mutation rate in LSCs could explain the fairly modest age-related increase reported previously for stem cellderived organoids (figs. S2B and S3C) (8). The tendency of differentiated hepatocytes to accumulate mutations to a much higher level than stem cells is further confirmed by the significantly higher cell-to-cell variation among the former (P = 1.42 103, Levenes test; Fig. 1, C and D). These observations are in keeping with the idea that stem cells are superior to differentiated cells in preserving their genome integrity, possibly through an enhanced capability to prevent or repair DNA damage (21, 22).

Next, we analyzed the mutational spectra in LSCs and differentiated hepatocytes. In differentiated hepatocytes, the most common mutation types were GC-to-AT transitions and GC-to-TA transversions (Fig. 2A and fig. S4, A and B). These mutations are known to be induced by oxidative damage (23), which itself has often been considered as a main driver of aging and age-related diseases (24). However, the most rapidly increased mutation type with age was the AT-to-GC transition (P = 2.16 1010, two-tailed Students t test; table S4 for Pearsons 2 test). This mutation can be caused by mispairing of hydroxymethyluracil (5-hmU), another common oxidative DNA lesion. Alternatively, AT-to-GC mutations are induced by mutagenic alkyl-DNA adducts formed as a result of thymine residue alkylation (25, 26). Notably, certain minor alkyl-pyrimidine derivatives can escape repair, accumulate during aging, and lead to mutations much later (26, 27).

(A) Relative contribution of the indicated six mutation types to the point mutation spectrum for the five indicated liver sample groups. Data are represented as the mean relative contribution of each mutation type in sample groups of young and aged differentiated hepatocytes (21 cells from six donors 36 years, and 23 cells from six donors 46 years), adult LSC-derived parent clones and their kindred single cells separately, and a group of outlier cells (n = 4). (B) Three mutational signatures (L1, L2, and L3) were de novo identified by non-negative matrix factorization analysis from the somatic mutations in the different groups in (A). (C) Contributions of signatures L1, L2, and L3 to all SNVs in young and aged hepatocytes, young LSCs, and outlier cells.

Mutation spectra of the LSCs and LSC clones revealed a lower fraction of GC-to-AT transitions as compared with differentiated hepatocytes from the young group (Fig. 2A and figs. S3D and S4, A and B). This could be due to the virgin state of these cells, not participating in metabolizing xenobiotics, which is associated with oxidative DNA damage. However, we cannot rule out that, instead, the altered spectrum is related to in vitro culturing, which may alter the ratio of GC-to-AT transitions and GC-to-TA transversions. In the human LSCs derived from clones, the relative frequency of the GC-to-AT transition mutations is slightly, albeit significantly, increased as compared with the parent clones themselves (P = 7.43 104, two-tailed Students t test; table S4 for Pearsons 2 test; Fig. 2A and fig. S4A). Kindred single LSCs, which were derived from parent LSC clones, representing the original LSCs, have undergone multiple rounds of cell division with ample opportunity for replication errors, for example, as a consequence of ambient oxygen to which these cells have been inevitably exposed during subculture. Hence, this would suggest that cell culture has the opposite effect of what we observed from the stem cell versus differentiated cell difference, i.e., increasing rather than decreasing the fraction of GC-to-AT transitions.

To analyze mutation spectra more precisely, we performed non-negative matrix factorization (Materials and Methods) to extract three de novo mutation signatures, signatures L1, L2, and L3, from the mutation spectra of the four groups of human liver cells analyzed, i.e., combined LSCs and clones collectively, differentiated hepatocytes from young participants, differentiated hepatocytes from aged participants, and the four combined outlier cells. We compared these signatures to the COSMIC (Catalogue Of Somatic Mutations in Cancer) signatures described for various human tumors (Fig. 2B and table S5). Signature L1 substantially increased in differentiated hepatocytes from the aged group as compared with hepatocytes and LSCs from young individuals (Fig. 2C). This signature highly correlated with the liver-specific and age-associated mutation signature A dominant in human organoids of liver-specific origin in the aforementioned organoid study (8), as well as with COSMIC signature SBS5, strongly associated with aging (fig. S4C and table S5) (28, 29). Signature L2, with its increased level of oxidative GC > TA transversions, dominated the mutation spectrum of both LSCs and differentiated hepatocytes from young donors (Fig. 2C) and was significantly reduced in cells from the aged donors. Signature L2 highly correlated with COSMIC signatures SBS18 and SBS36, known to be associated not only with oxidative stress (fig. S4C and table S5) but also with proliferation signature C (table S5), found in all in vitro propagated cell types in the aforementioned organoid study (8). Since this signature was dominant in the LSCs, it possibly reflects the stem/progenitor-like origin of hepatocytes and remains dominant in differentiated hepatocytes of the young individuals (Fig. 2C). Signature 3, dominant in the outlier cells, highly correlated with COSMIC signature SBS5, the aging signature, but also correlated with SBS6 and SBS1, signatures associated with DNA mismatch repair deficiency (29).

The above analysis was confirmed when we, instead of extracting de novo signatures from our four groups of liver cell mutation spectra, tested which of the reference COSMIC signatures could be found in these groups (fig. S4C).

Next, we analyzed the distribution of the somatic mutations in human liver cells across the genome. After pooling all mutations of the 21 differentiated cells from the young and the 23 differentiated cells from the old individuals, excluding the four outliers, the large majority of mutations distributed randomly across the genome in both groups (Fig. 3A). We then tested the possibility that during aging, mutations in functionally relevant sequences were selected against, as we previously observed for age-related mutation accumulation in B lymphocytes (7). Here, the functional liver genome was defined as the transcribed liver exome, using available data on gene expression levels in 175 previously described total liver samples [Genotype-Tissue Expression (GTEx) Consortium] (30), and its regulatory regions, identified as promoters of active genes or open chromatin regions, e.g., transcription factor binding regions, identified by ATAC (Assay for Transposase-Accessible Chromatin) sequencing in total liver tissue (ENCODE) (31). Of note, since the databases used were from whole liver, these definitions would not necessarily apply to LSCs or other subpopulations. However, it is reasonable to assume that whole liver is a good surrogate even for those fairly rare liver-specific cells.

(A) Circos diagram of genomic SNV distribution in four groups: pooled LSCs, young and aged hepatocytes, and outlier cells. (B) SNV levels in the functional genome and genome overall in differentiated hepatocytes (left) and in LSCs (right) as a function of age. Each data point represents the ratio of the number of mutations per cell to the median number of mutations of the four cells from the 5-month-old subject. Mutations in the functional genome are shown in red and those in the genome overall in blue. (C) Mutation frequency per base pair in the transcribed part of the liver genome (red) and the nontranscribed part (blue) in differentiated hepatocytes (left) and LSCs (right) as a function of age.

The ratio of total to functional SNVs in differentiated hepatocytes was found to remain about 1 across the different age levels (P = 0.5134, Wilcoxon signed-rank test, two tailed) (Fig. 3B), indicating no selection against deleterious somatic mutations in low-proliferating hepatocyte populations during aging. By contrast, the same ratio in pooled adult LSCs was about 2 and significantly different from that in differentiated hepatocytes (P = 5.34 104, Wilcoxon signed-rank test, two tailed). This suggests selection against deleterious mutations during the cell proliferation cycles that gave rise to these stem cells. It also suggests that LSCs may have an increased capacity to protect their genome simply by remaining quiescent. We also compared mutation frequencies in transcribed versus untranscribed liver cell genes. Transcribed liver genes were defined as genes with expression values 1 transcripts per kilobase per million (TPM), while nontranscribed genome included all sequences with expression values <1 TPM in liver tissue (GTEx) (30). The results indicated a significantly lower number of SNVs affecting transcribed liver genes than nontranscribed genes across all donor ages (P = 7.21 108, Wilcoxon signed-rank test, two tailed) as well as in the LSCs and clones (P = 7.63 106, Wilcoxon signed-rank test, two tailed) (Fig. 3B), suggesting active transcription-coupled repair in normal human liver (32).

Somatic mutations have long been implicated as a cause of aging (33, 34). However, thus far, it has not been possible to test this hypothesis directly because of a lack of advanced methods to analyze random somatic mutagenesis in vivo, which requires high-throughput sequencing of single cells. Using our advanced single-cell sequencing method, we show that the number of somatic base substitution mutations in normal human liver significantly increases with age, reaching as much as 3.3 times more mutations per cell in aged humans than in young individuals. Of note, the numbers of mutations in aged liver are significantly higher than what has previously been reported for aged human liver organoids (fig. S2B) (8) and also higher than recent results reported for aged human neurons (fig. S2A) and B cells (7). Since we essentially ruled out that many of these mutations are artifacts of the amplification system, the most likely cause of this high mutagenic activity in the human liver is the high metabolic and detoxification activity in this organ, which is known to be associated with genotoxicity (35).

Out of 48 hepatocyte cells analyzed, 4 cells revealed extremely elevated mutation loads, over 10 times exceeding SNV levels in age-matched normal hepatocytes even from the same subject. These outliers have also been observed in the only two studies of somatic mutations in human tissues in vivo using a single-cell WGS approach (6, 7). Of the four outliers observed in this present study, multiple de novo SNVs were found to reside in DNA repair genes, strongly suggesting that these mutations were responsible for mutator phenotypes similar to what has been shown for cancers (36). While we cannot know when the mutations that gave rise to rapid mutation accumulation in these cells occurred, this may have been fairly recently, with imminent death of the cells likely. On average, almost 60 nonsynonymous mutations in the functional exome of these cells were found, suggesting a likely functional effect (table S6). However, since we could not longitudinally follow mutation loads in the same single cells, our data do not allow any conclusions on the cause and effect of the observed mutations.

Somatic mutation frequencies in normal differentiated hepatocytes were found to be much higher than in residential LSCs. This means that in vitro clonal surrogates for cells do not always accurately represent the mutation loads of in vivo differentiated cells, which makes predictions of a functional impact of somatic mutations from these clonal data difficult. While we do not know the mechanism(s) of reduced spontaneous mutation loads in stem as compared with differentiated cells, such evidence has also been reported by others (18, 19), and it is possible that stem cells have superior genome maintenance systems as compared with their differentiated counterparts. However, a caveat in this respect is that the LSCs that we enriched for may not in fact be the LSCs giving rise to most of the differentiated hepatocytes. Hence, we cannot be sure that a direct comparison between a stem cell and differentiated cells derived from this stem cell was in fact made.

Another important question is the possible functional impact of random somatic mutagenesis on the aging phenotype. While from our current data we cannot conclude direct cause-and-effect relationships, our observation that the functional part of the genome accumulated numerous mutations suggests that aging-related cellular degeneration and death could at least, in part, be due to somatic mutations. While the occurrence of no more than 11 nonsynonymous mutations in the transcribed exome of liver hepatocytes from humans in their 70s suggests a minor contribution of changes in the protein-coding part of the genome, the well over 100 de novo mutations in gene regulatory sequences may point toward an important role for stochastic gene expression changes in age-related loss of organ function and increased disease incidence. These mutations could possibly increase transcriptional noise, a molecular phenotype that appears characteristic for cells from aged individuals (3739).

Last, while in our current work only base substitution mutations were analyzed, other types of mutations are likely to occur as well. The frequency of most of these mutations, e.g., small insertions and deletions, copy number variation, and genome structural variation, is likely to be much lower than the frequencies of base substitutions observed to rise to thousands of mutations per cell. However, their effects are possibly much larger since they affect a larger part of the genome and, when in exomes, almost always lead to loss of function. It is conceivable that, taken together, de novo mutations could have serious effects on the function of human somatic cells in vivo above and beyond their causal relevance in liver cancer.

Frozen human hepatocyte samples were purchased from Lonza Walkersville Inc. Whole livers for hepatocyte isolation were obtained with the informed consent of families of registered organ donors. The obtained liver organs were rejected for transplant due to either lack of a donor match or morphological alterations (e.g., tearing and hematoma). All 12 selected hepatocyte donors were healthy participants of various age, gender, and ethnicity (table S1) without any liver cancer or other liver pathology history. These cells had been isolated using a gold standard, two-step liver/liver lobe perfusion procedure. Cells were suspended in 2 to 5 ml of media and counted with Trypan blue to estimate viability (higher than 80%), and frozen in dimethyl sulfoxide/liquid nitrogen (www.lonza.com). One specimen of frozen human neonatal LSCs from a 1-year-old donor was purchased from Kerafast Inc. (www.kerafast.com). These cells had been derived by the Sherley laboratory (Boston, MA, USA) and characterized to confirm their stem cell identity (4042).

After thawing, hepatocyte suspensions were used to collect single hepatocytes into individual 0.2-ml PCR tubes with 2.5 l of phosphate-buffered saline (PBS) by means of FACS (FACSAria, Becton Dickenson). Selection of the target hepatocyte population was based on the large cell size of hepatocytes (forward-scatter/side-scatter parameters) along with the additional fluorescence staining for DNA content and cell viability. Briefly, bulk hepatocyte suspension samples were prior stained according to the manufacturers protocol with the viable DNA-binding dye Hoechst 33342 (Life Technologies) to discriminate cells with a standard diploid chromosome set and LIVE/DEAD Cell Vitality Assay Kit C12 Resazurin/SYTOX Green (Thermo Fisher Scientific) to select viable healthy cells. Typical FACS layout is shown in fig. S1A. Upon sorting, tubes with single cells were frozen on dry ice and kept at 80C until use.

Neonatal LSCs of passage 9 (one passage corresponds to approximately three cell population doublings for these cells according to the manufacturers protocol) from the 1-year-old donor were purchased from Kerafast Inc. The commercial LSCs were cultured in polarization media [Dulbeccos modified Eagles medium, 10% dialyzed fetal bovine serum (Invitrogen), 1.5 mM xanthosine (Sigma), 1 penicillin/streptomycin, epidermal growth factor human (20 ng/ml; Invitrogen), transforming growth factor human recombinant (0.5 ng/ml Sigma)] according to the manufacturers protocol (Kerafast Inc.) (4042). These cells served as controls to characterize de novo isolated and polarized LSCs.

Additional LSC cultures were isolated and polarized and characterized from the bulk commercial hepatocyte suspensions (Lonza Walkersville Inc.) from young donors using previously described protocols with specific modifications (15, 16) combined with the aforementioned Kerafast protocol for neonatal LSCs. Briefly, bulk suspension hepatocytes (0.5 106 to 1 106 of cells) were transferred to polarization media as described for the neonatal LSCs and cultured on cell-adhesive 12-well plates for 5 to 7 days. Then, all nonattached hepatocytes were removed, and fresh media were added to the small remaining population of attached progenitor cells. After 1 to 1.5 weeks of culture and media changes, attached cells symmetrically divided, growing to mixed clonal populations of polarized adult LSCs. These cultures were frozen at early passage (p = 3 to 5) until further use. Only LSCs from donors of younger age (22 years) could be isolated in this way.

Phenotypes of the polarized cells were analyzed for the presence of specific surface stem cell and epithelial progenitor cell epitopes, e.g. EpCAM (epithelial cell adhesion molecule), Lgr5, CD90, CD29, CD105, and CD73, upon staining with antibodies by means of multicolor flow cytometry analysis (LSRII, Becton Dickinson) as recommended previously (15, 16, 43, 44). Characteristic FACS profiles and specific phenotypes for commercial LSCs (control) and two manually isolated and polarized LSC lineages are shown in fig. S1B.

Single-cell derived parent clones and their kindred single cells were prepared and collected using CellRaft arrays (Cell Microsystems) as described previously (11). Briefly, an LSC suspension was plated on a CellRaft array consisting of 12,000 individual portable rafts for single cells at the required density of 5000 cells per array. After 4 to 8 hours, individual LSCs were elongated and attached to the array surface locating on individual rafts. After attachment, the medium with floating cells was replaced, and single-cell positions were marked and tracked during the following 7 to 10 days to detect dividing cells and growing individual single-cell derived clones. Once the colony/clone reached confluence on the raft (8 to 10 cells per raft), it was dislocated from the array with a positioned automatic needle and transferred with a magnetic wand to a 96-well plate. Upon reaching confluence, single-cell derived clones were trypsinized and subsequently transferred to 24-well plates, then 12-well plates, 6-well plates, and, lastly, 10-cm plates to reach a total amount of 1.5 106 to 3 106 cells per parent clone. Together, the process of establishing a clone from a single cell took about 25 to 30 days.

Individual single cells from the parent clones were collected, also using CellRafts, and transferred to a 0.2-ml PCR tube containing 2.5 l of PBS. The presence of a single raft was observed under a magnifying glass. Upon single-cell collection, tubes were fast frozen on dry ice and kept on 80C until further use.

Single hepatocytes from each subject were subjected to WGA using our modified procedure of low-temperature cell lysis and DNA denaturation followed by MDA as described (11). As positive and negative controls for WGA, we used 1 ng of human genomic DNA and DNA-free PBS solution, respectively. Resultant MDA products were purified using AMPureXP beads (Beckman Coulter), and the amplified DNA concentration was measured with the Qubit High Sensitivity dsDNA kit (Invitrogen Life Sciences). To verify sufficient and uniformly amplified single-cell MDA products, we performed the eight-target locus-dropout test as described previously (11). Selected confirmed samples (four single-cell MDA products per subject) were further subjected to library preparation and WGS.

Human bulk genomic DNA was collected from total cell suspensions using the DNeasy Blood & Tissue Kit (Qiagen) according to the manufacturers protocol. LSC clonederived DNA was extracted from clones of at least 1.5 106 to 2.5 106 cells in a similar way. DNA concentration was quantified with the Qubit High Sensitivity dsDNA kit (Invitrogen Life Sciences), and DNA quality was evaluated by 1% agarose gel electrophoresis.

The libraries for Illumina next-generation WGS were generated from 0.2 to 0.4 g of genomic DNA, clone-derived bulk DNA, and single-cell MDA DNA human samples using the NEBNext Ultra II FS DNA Library Prep Kit for Illumina (New England BioLabs). The libraries were sequenced with 2 350base pair paired-end reads on an Illumina HiSeq X Ten sequencing platform by Novogene Inc.

Next-generation WGS at a minimal depth of 20X base coverage was performed on four individual mature hepatocytes per human subject (12 human subjects, 48 single cells in total) (table S2). Bulk DNA from two or three LSC-derived clones and MDA products from three to four corresponding kindred single cells per donor (three donors, eight parent clones, and 10 kindred single LSCs) were sequenced similarly.

For all samples, adapter and low-quality reads were trimmed by Trim Galore (version 0.3.7). Quality checks were performed before and after read trimming by FastQC (version 0.11.4). The trimmed reads were aligned to the human reference genome (GRCh37 with decoy) by BWA mem (version 0.7.10) (45). Duplications were removed using samtools (version 0.1.19) (46). The known indels and single-nucleotide polymorphism (SNPs) were collected from the 1000 Genomes Project (phase 1) and Single Nucleotide Polymorphism Database (dbSNP) (build 144). Then, the reads around known indels were locally realigned, and their base quality scores were recalibrated on the basis of known indels and SNVs, both via the Genome Analysis Toolkit (GATK, version 3.5.0) (47).

Somatic mutations between each single cell and the corresponding bulk and between each clone and corresponding bulk were identified using three different variant callers: VarScan2 (48), MuTect2 (49), and HaplotypeCaller (47). To obtain high-quality mutation calls and avoid high false-positive rates in individual callers, we applied a comprehensive procedure in filtering. First, we only considered mutations on autosomes. Then, we considered mutations with a GATK phred-scaled quality score of at least 30 and excluded mutations overlapping with known SNPs from dbSNP. Furthermore, we required a minimum base depth of 20X and filtered mutations with variant-supporting reads in bulk. Moreover, mutations present in at least two cells in each individual were also removed to further exclude potential germline mutations. The mutations present in all three variant callers were considered as true de novo mutations. Last, considering that amplification errors and/or nonuniform coverage could induce false-positive mutations in no more than one-eighth of the reads, we used a binomial distribution to filter these potential false-positive mutations, which excluded most mutations present in 25% of the reads or less. To further check the power of the used pipeline in filtering amplification errors, we also called the somatic mutations using our alternative, the SCcaller tool (11) and the LiRA pipeline (13) (figs. S2A and S3B).

The frequency of somatic SNVs per cell was estimated after normalizing genomic coveragefrequency of somatic SNVs per cell=#somatic SNVssurveyed genometotal size of genome

As the reads were aligned to the haploid reference genome, the frequency of somatic SNVs per base pair was calculated by dividing the frequency of somatic SNVs per cell by genome size and ploidy of the genome (ploidy = 2)frequency of somatic SNVs per base pair=frequency of somatic SNVs per celltotal size of genome*ploidy of genome

The surveyed genome per single cell/clone was calculated as the number of nucleotides with read mapping quality 20 and position coverage 20X.

The outliers of the hepatocytes were defined using Tukeys range test: Four cells were defined as extreme outliers as their frequencies were higher than Q3 + 3 * IQR, where Q3 is the third quartile of the frequencies and IQR is the interquartile range. The outlier cells were excluded from the statistical model.

For the LSC-differentiated hepatocyte comparison, the absolute de novo mutation frequencies were corrected for the number of cell divisions undergone since the zygote (table S2). We used 45.1 as the number of developmental mitoses (20) and assumed a subsequent turnover rate of one cell division per year, based on empirical evidence from rodents (50, 51). In total, 45.5, 46.3, and 61.6 cell divisions were estimated for both LSCs and differentiated hepatocytes from 5-month-old, 1-year-old, and 18-year-old individuals, respectively. For LSCs from 5-month-old, 1-year-old, and 18-year-old individuals, we then added, respectively, an estimated 33, 41.7, and 33 cell divisions during the enrichment process of stem cells, and 21.9, 24.5, and 21.9 cell divisions associated with clonal outgrowth of the single LSCs.

To determine the overlap between SNVs called in the clones and the single cells derived from them, genome coverage in the clone was normalized to that in its kindred single cell. Mutations found in a single cell and appearing in at least 1 read in the parent clone were considered as overlapping. When there were no variant-supporting reads in the clone, the mutation was determined as kindred cell specific. This assignment left some mutations with an unknown status more likely to be de novo mutations arising in the individual cells during clone culture and expansion.

The identified mutations in all individuals were pooled into four groups: LSC cells/clones from young donors, hepatocytes from young and aged donors, and outlier hepatocytes. The integrated spectra of six mutation types in each group were plotted using the R package MutationalPatterns (52). Using non-negative matrix factorization (NMF) decomposition in the same package, we revealed group-specific mutational signatures as well as de novo identified three signatures in normal human liver cells. To identify the potential origin of the mutational spectra, the group mutational signatures and newly revealed signatures to the published signatures associated with liver-specific organoids and various cancer tissues. Three tissue-specific organoid signatures were obtained from a recent study (8); 67 cancer mutation signatures were downloaded from the latest version 3 of the COSMIC database (https://cancer.sanger.ac.uk/cosmic/signatures/SBS/) (28, 29). The cosine similarity between newly identified and published signatures was calculated for comparisons (table S5).

All reported mutations were annotated based on the gene definitions of GRCh37.87. Mutations were further extracted from the functional genome, including transcribed genes, promoters, and open chromatin regions. The nonsynonymous and synonymous mutations were identified by analysis of variance (ANOVA) (53), while damaging and tolerated mutations were checked by SIFT (54) and PROVEAN (55). When damaging (Sorting Intolearnt From Tolerant, SIFT) or deleterious (Protein Variation Effect Analyzer, PROVEAN), the mutation was marked as damaging, and when tolerated (SIFT) and neutral (PROVEAN), a tolerated mutation.

The open chromatin regions were identified by ENCODE transcription factor binding regions in whole genome and ATAC sequencing data in the functional genome in liver tissue samples. Raw ATAC sequencing data were downloaded from ENCODE (experiment name: ENCSR373TDL) (31). The adapter and low-quality ATAC sequencing reads were filtered using Trim Galore (version 0.3.7). Clean reads were aligned to the human reference genome (GRCh37) with Bowtie2 (version 2.2.3; option: -X 2000). Duplicated reads were removed with the Picard tool (version 1.119). Open chromatin regions were determined by MACS2 (version 2.1.1; option: callpeak -g hs --nomodel --shift 100 --extsize 200) (56).

Gene expression levels for total human liver tissue were obtained from GTEx (https://gtexportal.org/) (30). We defined the transcribed genes as those with expression level 1 TPM in all samples. Also, we separated the transcribed and nontranscribed genome by TPM 1 and < 1 in all samples, respectively.

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Single-cell analysis reveals different age-related somatic mutation profiles between stem and differentiated cells in human liver - Science Advances

Lab-grown snake venom glands are here. Dont worry; theyre for a good cause – Digital Trends

Every year, the equivalent of the total population of Tuscaloosa, Alabama slightly more than 100,000 people die worldwide as a result of snake bites. Provided a snake bite victim is able to get to the emergency room quick enough, antivenom can be used to counter the deadly effects of a bite. But antivenom isnt easy to manufacture. Its made by collecting venom from venomous snakes and injecting small quantities of it into a domestic animal such as a horse. The antibodies that form can then be collected from the horses blood and purified to make a finished antivenom. So far, so straightforward.

The problem is getting hold of enough venom to make it. Antivenom is currently manufactured by catching or breeding snakes, keeping them in captivity, and then regularly milking them to gather the venom they produce. Its a 19th century treatment thats made necessary by the fact that antivenom production has not developed as fast as other areas of biotechnology. With 600 species of venomous snake, its also a labour-intensive job which nonetheless struggles to create antidotes enough to meet the number of annual snake bites. Could genetic engineering be the answer?

A group of three researchers at Utrecht University in the Netherlands think so. And their idea for achieving it is kind of brilliant. Rather than creating lab-grown venomous snakes an idea that, frankly, would only sound good to one of the screenwriters of Sharknado theyve come up with an alternative solution: Simply grow the part of the snake that you need.

We were thinking about novel areas for [our] organoid technology, Hans Clevers, whose lab carried out the work, told Digital Trends. Snake venom glands were the most fascinating tissue to us. A main first hurdle was to obtain snake tissue. Luckily, a collaboration with snake experts Michael Richardson and Freek Vonk, as well as the Dutch reptile zoo Serpo and local breeders solved this issue. After some months of optimizing the protocols, we were successful in growing miniature venom glands. Since then, we have been optimizing the protocol to produce venom and have characterized the cells which make the toxins.

Aspidelaps lubricus hatching (individuals not used in study) Jeremie Tai-A-Pin

An organoid, for those unfamiliar with it, is a miniaturized and simplified version of an organ, complete with realistic micro-anatomy. Theyre made using stem cells, which let them self-organize in a three-dimensional culture to transform into the organ theyre supposed to replicate. The emerging organ is a clump of cells around 1 millimeter across. Organoids have been created by various labs around the world, approximating organs that range from kidneys to miniature, non-conscious brains. In this case, the venomous organoids resemble a tiny pea-sized balloon filled with liquid. One that would be particularly inhumane to fire across the classroom like a spitball wad.

Our group has been successful in the past 10 years in growing organoids from a variety of human tissues, Joep Beumer, another researcher on the project, explained. To generate these, we harvest stem cells from adult tissue and embed them into a gel in a petri dish. With the right growth factor mix, the stem cells will divide and give rise to mini-organs containing the different cell types of one tissue.

The tissue samples for the venom organoids were taken from gland tissue from snake embryos inside eggs or, in one instance, from a pet snake which had been put down as a result of illness. To grow the gland organoids, the team had to make a few changes to their normal approach. Snakes are cold-blooded. Mammalian organoid protocols are normally grown at a temperature of 37 degrees Celsius (99 degrees Fahrenheit). Unfortunately, this didnt work for the snake organoids. At this temperature, the organoids suffered heat shock response and died. As a result, they had to lower the temperature to 32 degrees Celsius. Its a demonstration of how, even at this scale, the concepts and signaling pathways of adult stem cells are conserved in organoids.

Every tissue has its own characteristics which we aim to model with organoids, said Yorick Post, the third researcher on the project. For the snake venom gland this was a very obvious case: would they make venom? We knew that the potential of this technology would hinge greatly on the ability to produce the different toxins which constitute snake venom. So we were very excited when we found toxins first on RNA, and later on [the] protein level.

This work is extremely promising. The researchers think it could potentially go beyond just cutting out the snake-farming part of the antivenom process as well. They believe it might be possible to grow the immune cells that are usually produced by animals inside a dish. Alongside antivenom, the approach could also be useful for helping develop drug compounds based on components found in snake venom. For instance, theres a certain type of blood pressure medicine thats created from a toxin produced by the venomous Brazilian pit viper.

And as to, no pun intended, the scaling up part of the project? This is one of the main advantages of organoid technology, Clevers said. Once established, we can expand the tissue [in a] pretty much unlimited [manner]. This can help to preserve viable cells of many snake species, as they can be frozen and thawed easily. [It can also help us] generate large numbers of venom producing cells. Further improvements in venom production and harvesting will be needed to make this approach cost efficient. We are actively working towards these aims.

A paper describing the work was recently published in the journal Cell.

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Lab-grown snake venom glands are here. Dont worry; theyre for a good cause - Digital Trends

Space might be the perfect place to grow human organs – Popular Science

Three-dimensional printers have now assembled candy, clothing, and even mouse ovaries. But in the next decade, specialized bioprinters could begin to build functioning human organs in space. It turns out, the minimal gravity conditions in space may provide a more ideal environment for building organs than gravity-heavy Earth.

If successful, space-printed organs could help to shorten transplant waitlists and even eliminate organ rejection. Though they still have a long way to go, researchers at the International Space Station (ISS) hope to eventually assemble organs from adult human cells, including stem cells.

The medical field has only recently embraced 3D printing in general, particularly in biomedical fields like regenerative medicine and prosthetics. So far, these printers have produced early versions of blood vessels, bones, and different types of living tissue by churning out repeated layers of bioinka substance comprised of living human cells and other tissue thats meant to mimic the natural environment that surrounds growing organs.

Recently, researchers are finding that Earth might not be the best environment for growing freestanding organs. Because gravity is constantly pushing down on these delicate structures as they grow, researchers must surround the tissues in scaffolding, which can often debilitate the delicate veins and blood vessels and prevent the soon-to-be organs from growing and functioning properly. Within microgravity, however, soft tissues hold their shape naturally, without the need for surrounding supportan observation thats driven researchers to space.

And one manufacturing lab based in Indiana thinks its tech could play a key role in space. The 3D BioFabrication Facility (BFF) is a specialized 3D printer that uses bioink to build layers several times thinner than human hair. It cost about $7 million to build and employs the smallest print tips in existence.

The brainchild of spaceflight equipment developer Techshot and 3D printer manufacturer nScrypt, the BFF headed to the ISS in July 2019 aboard the SpaceX CRS-18.

Currently, the project focuses on building increasingly thick artificial cardiac tissue and delivering it back to Earth. Once the printed cardiac tissue reaches a certain thickness, it gets harder for researchers to ensure that a printed structures layers effectively grow into one another. Ultimately, though, theyd like the organs to arrive here fully formed.

Printed organs would eventually require vasculature and nerve endings to work properly, though that technology doesnt yet exist.

The next stagetesting heart patches under microscopes and within animalscould span over the next four years. As for whole organs, Techshot claims it plans to begin production after 2025. For now, the project is still in its infancy.

If you were to look at what we printed, it looks very modest, says Techshot vice president of corporate advancement Rich Boling. Its just a cuboid-type shape, this rectangular box. Were just trying to get cells to grow one layer into the next.

Cooking organs like pancakes

Compare the manufacturing process to cooking pancakes, Boling says. The space crew first creates a custom bioink pancake mix with the cells sent from Earth, which they load with syringe-like tools into the BFF.

Researchers then insert a cassette into the BFF containing a bioreactora system that mimics the normal bodily functions essential for growing healthy tissue, like providing nutrients and flushing out waste.

Approximately 200 miles below in Greenville, Indiana, Techshot engineers connect with ISS astronauts on a NASA-enabled secure digital pathway. The linkup allows Techshot to remotely command BFF functions like pump pressure, internal temperature, lighting, and print speed.

Next, the actual printing process occurs within the bioreactor and can take anywhere from moments to hours, depending on the shapes complexity. In the final production step, the cell-culturing ADvanced Space Experiment Processor (ADSEP) cooks the theoretical pancake; essentially, the ADSEP toughens up the printed tissue for its journey back to earth. This step could take anywhere from 12 to 45 days for different tissue types. When completed and hardened, the structure heads home.

The researchers have gone through three testing processes so far, each one getting more exact. This March, theyll begin the third round of experiments.

The bioprinter space race

The BFF lab is the sole team developing this specific type of microgravity bioprinter, Boling says. Theyre not the only ones looking to print human organs in space, though.

A Russian project has also entered the bioprinting space race, however their technique highly differs. Unlike the BFFs bioink layering method, Russian biotechnology laboratory 3D Bioprinting Solutions uses magnetic nanoparticles to produce tissue. An electromagnet creates a magnetic field in which levitating tissue forms the desired structuretechnology that appears ripped from the pages of a sci-fi novel.

After their bioprinter fell victim to an October 2018 spacecraft crash, 3D Bioprinting Solutions rebounded; the team now collaborates with US and Israeli researchers at the ISS. Last month, their crew created the first space-bioprinted bone tissue. Similar to the US project, 3D Bioprinting Solutions aims to manufacture functioning human tissues and organs for transplantation and general repair.

Just because we have the technology to do it, should we do it?

If the 3D BioFabrication Facility prospers in printing working human organs, theyd be subject to thorough regulation here on Earth. The US approval process is stringent for any drug, Rich Boling says, posing a challenge for this unprecedented invention. Techshot predicts at least 10 years for space-printed organs to achieve legal approval, though its an inexact estimate.

Along with regulatory acceptance, human tissue printed in microgravity may encounter societal pushback.

Each country maintains varying laws related to medical transplants. Yet as bioengineering advances into the the final frontier, the international scientific research community may need to shape new guidelines for collaboration among the stars.

As the commercialization of low-Earth orbit continues to ramp up in the next few years, it is certainly true that were going to have to take a very close look at the regulations that apply to that, says International Space Station U.S. National Laboratory interim chief scientist Michael Roberts. And some of those regulations are going to stray into questions related to ethics: Just because we have the technology to do it, should we do it?

Niki Vermeulen, a University of Edinburgh science technology and innovation studies lecturer, has researched the social implications of 3D bioprinting experiments. Like any Earth-bound project, she urges scientists not to get peoples hopes up too early in the process; individuals seeking organ transplants could read about the BFF online and think it could soon be ready to meet their needs.

The most important thing now, I think, is expectation management, Vermeulen says. Because its really quite difficult to do this, and of course we really dont know if its going to work. If it did, it would be amazing.

Another main issue is cost. Like other cutting-edge biotechnology innovations, the organs could also pose a major affordability challenge, she says. Techshot claims that a single space-printed organ could actually cost less than one from a human donor, since some people must pay for a lifetime of anti-rejection meds and/or multiple transplants. Theres currently no telling how long the BFF process would actually take, however, compared to the conventional donor route.

Plus, theres potential health risks for recipients: Techshot chief scientist Eugene Boland says cell manipulation always presents a possibility of genetic mutation. Modified stem cells can potentially cause cancer in recipients, for example.

The team is now working to define and minimize any dangers, he says. The BFF experiment adheres to the FDAs specific regulations for human cells, tissues, and cellular and tissue-based products.

Researchers on the ground now hope to perfect human cell manipulation: Over 100 US clinical trials presently test cultured autologous human cells, and several hundred test cultured stem cells with multiple origins.

What comes next

After the next round of printing tests this March, Techshot will share the bioprinter with companies and research institutions looking to print materials like cartilage, bone, and liver tissue. Theyre currently preparing the bioprinter for these additional uses, Boling says, which could advance health care as a whole.

To speed things up for space crews, Techshot is now building a cell factory that produces multiple cell types in orbit. This technology could cut down the number of cell deliveries between Earth and space.

The ISS has taken in plenty of commercial ventures in recent years, Michael Roberts says, and its getting crowded up there. Space-based experiments ramped up between 40 and 50 years ago, though until recently they mostly prioritized satellite communications and remote observation technology. Since then, satellites have shrunk from bus-sized to smaller than a shoebox.

Roberts has witnessed the scientific areas of interest broaden over the past decade to include medicine. Organizations like the National Institutes of Health are now looking to space to improve treatments, and everything from large pharmaceutical companies to small-scale startups want in.

Theyve got something stuck on every surface up there, he says.

As the ISS runs out of space and exterior attachment points, Roberts predicts that commercial ventures will build new facilities built for specific activities like manufacturing and plant growth. He sees it as a good opportunity for further innovation, since the ISS was originally designed for far more general purposes.

Space, as a whole, may start to look quite different from the first exploration age.

Baby boomers may remember glimpsing at a grainy, black-and-white moon landing five decades ago. Within the same lifetime, they could potentially observe the introduction of space-printed organs.

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Space might be the perfect place to grow human organs - Popular Science

Injection Innovation May Improve Spinal Cord Repair Research – Technology Networks

An international research team, led by physician-scientists at University of California San Diego School of Medicine, describe a new method for delivering neural precursor cells (NSCs) to spinal cord injuries in rats, reducing the risk of further injury and boosting the propagation of potentially reparative cells.NSCs hold great potential for treating a variety of neurodegenerative diseases and injuries to the spinal cord. The stem cells possess the ability to differentiate into multiple types of neural cell, depending upon their environment. As a result, there is great interest and much effort to use these cells to repair spinal cord injuries and effectively restore related functions.

But current spinal cell delivery techniques, said Martin Marsala, MD, professor in the Department of Anesthesiology at UC San Diego School of Medicine, involve direct needle injection into the spinal parenchyma the primary cord of nerve fibers running through the vertebral column. "As such, there is an inherent risk of (further) spinal tissue injury or intraparechymal bleeding," said Marsala.

The new technique is less invasive, depositing injected cells into the spinal subpial space a space between the pial membrane and the superficial layers of the spinal cord.

"This injection technique allows the delivery of high cell numbers from a single injection," said Marsala. "Cells with proliferative properties, such as glial progenitors, then migrate into the spinal parenchyma and populate over time in multiple spinal segments as well as the brain stem. Injected cells acquire the functional properties consistent with surrounding host cells."

Marsala, senior author Joseph Ciacci, MD, a neurosurgeon at UC San Diego Health, and colleagues suggest that subpially-injected cells are likely to accelerate and improve treatment potency in cell-replacement therapies for several spinal neurodegenerative disorders in which a broad repopulation by glial cells, such as oligodendrocytes or astrocytes, is desired.

"This may include spinal traumatic injury, amyotrophic lateral sclerosis and multiple sclerosis," said Ciacci.

The researchers plan to test the cell delivery system in larger preclinical animal models of spinal traumatic injury that more closely mimic human anatomy and size. "The goal is to define the optimal cell dosing and timing of cell delivery after spinal injury, which is associated with the best treatment effect," said Marsala.ReferenceMarsala et al. (2019) Spinal parenchymal occupation by neural stem cells after subpial delivery in adult immunodeficient rats. Stem Cells Translational Medicine. DOI: https://doi.org/10.1002/sctm.19-0156

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Injection Innovation May Improve Spinal Cord Repair Research - Technology Networks

Robots don’t have to be so embarrassing – The Outline

Robots are pathetic. You need only watch a robot soccer fail compilation to see that humans ancient quest to build synthetic replicas of ourselves out of nuts, bolts and wiring has been a bust. Every new, groundbreaking robot inevitably turns out to be an ungodly abomination, either physically inept or utterly incapable of social interaction. Our latest attempt at a full-on humanoid, Sophia, looks like a pre-loved department store mannequin and sounds like a 2007-era chatbot dialed to the VERY DEPRESSED setting. Shed be a walking repudiation of brainless techno-optimism, if she could actually walk.

Even attempts to build simpler, dog-like droids, such as Boston Dynamics Spot, have produced robots barely worthy of the name. They dont look much better than what youd expect from an adult Erector set enthusiasts weekend garage projects. Some people find these things terrifying, but I take my cues from the manufacturers, who seem incredibly proud when one of their creations performs a task as easy as opening a door.

Imitating human intelligence in software has also proven a task more difficult than expected. Despite the well-financed wet dreams of companies like Uber, the automotive industry has begun to quietly admit that truly self-driving cars are going to happen in decades, not just a few years from now. The Blue Brain project, which received a billion euros from the EU in 2013 and promised to simulate a human brain by 2019, did not succeed. Blue Brain seems to have had some success building a 3D atlas of a mouse brain, but the projects supercomputer, which takes up an entire room, is heaving and groaning under the strain of doing the same for a human mind. Valiant efforts to simulate a transparent, one millimetre nematode called C. elegans, ongoing since 2004, have yielded similarly slow progress. C. elegans has 302 neurons. The human brain has 86 billion.

These stuff-ups are endlessly amusing to me. I dont want to mock the engineers who pour thousands of hours into building novelty dogs made of bits of broken toasters, or even the vertiginously arrogant scientists who thought they could simulate the human brain inside a decade. (Inside a decade! I mean, my god!) Well, okay, maybe I do want to mock them. Is it a crime to enjoy watching our cultures systematic over-investment in digital Whiggery get written down in value time and time again?

On the other hand, maybe the people doing this stuff have just figured out that attaching the terms robot or artificial intelligence to whatever youre up to is a great way of attracting investment from rich idiots. Sometimes I feel naive for thinking anyone takes these wild claims seriously, but that is precisely the power of a good ideology. The promises of robotics and AI are so seductive that people suspend their critical faculties. Whether you are a business like Uber striving to eliminate the messy and expensive production input known as human beings, or a normal person desperate for easy transportation or someone to keep your elderly relatives company, the way we talk about robots and AI suggests these smart solutions are just around the corner. Even people with their heads screwed on properly dont seem to understand how credulously the media hypes up their coverage of AI.

What these doomed overreaches represent is a failure to grasp the limits of human knowledge. We dont have a comprehensive idea of how the brain works. There is no solid agreement on what consciousness really is. Is it divine? Is it matter? Can you smoke it? Do these questions even make sense? We dont know the purpose of sleep. We dont know what dreams are for. Sexual dimorphism in the brain remains a mystery. Are you picking up a pattern here? Even the seemingly quotidian mechanical abilities of the human body running, standing, gripping, and so on are not understood with the scientific precision that you might expect. How can you make a convincing replica of something if you dont even know what it is to begin with? We are cosmic toddlers waddling around in daddys shoes, pretending to work at the office by scribbling on the walls in crayon, and then wondering where our paychecks are.

The world is an astonishing place, and the idea that we have in our possession the basic tools needed to understand it is no more credible now than it was in Aristotles day, writes philosopher Thomas Nagel. But accepting this epistemic knuckle sandwich doesnt mean abandoning the pursuit of robotics.

Enter the frogbot, a living machine synthesized by a research team at the Allen Discovery Center at Tufts University in Boston.

Frogbots (called xenobots by their creators, a stupid name I refuse to use), are tiny little artificial animals made out of stem cells from the African clawed frog. They cant do much yet move around on two stumpy legs, carry tiny objects in a pouch but to me, they are stranger and scarier than any robot weve made out of metal and plastic.

A "frogbot" developed by researchers at Tufts University.

There are three basic steps to the frogbot process. First, stem cells that will develop into frog skin and frog heart are grown in a dish. (The proto-heart cells produce rhythmic contractions, which is how the finished frogbots move around.) Second, a computer runs an algorithm that simulates thousands and thousands of different frogbot designs in a virtual environment to see which ones are capable of whatever action you want them to perform. Finally, the designs that are likely to work are physically produced from clusters of stem cells using microsurgery, then let loose in another dish to see what they actually do. So far, they do pretty much whatever we want them to do, within reason.

This is very cool. Even though frogbots are tiny and stupid at the moment, they impress me way more than the conga line of faildroids weve managed to cobble together so far. Of course it makes sense to use materials from existing animals; weve been doing this using selective breeding techniques since the dawn of time. What are pigs or cows or sheep but frogbots built over thousands of years? The key innovation here is modelling selective evolution quickly, instead of standing around like idiots for millenia, waiting for hundreds of generations of dogs to fuck.

It makes perfect sense. Why try to reinvent the wheel when you could simply hijack biological processes that already exist? This is a classically human way of solving a problem, cleverer and yet also lazier than the futile pursuit of purely artificial robotics. A big congratulations to the scientists who figured this out, using only keen wit, a positive attitude, and a gigantic pile of money from the U.S. military research agency.

Yes, naturally this exciting new field of science is being used to develop weapons of war. This, not simply the prospect of new intelligences, is the upsetting thing about groundbreaking developments in robotics and AI. Will frogbots be a military invention that simply slides into everyday life, like the internet, canned food, and microwaves? Or will they be used to administer dangerous MKULTRA hallucinogens to innocent populations America decides are in its way? In a world controlled by a small and powerful elite that can essentially do whatever it wants, were forced to be suspicious of new technologies. Will the frogbot become bigger, smarter, and stronger? Yes, probably. Will it be my comrade? Thats another question entirely.

Eleanor Robertson is a writer and editor from Sydney, Australia.

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Robots don't have to be so embarrassing - The Outline