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Biology subjects

Jin, B.

Publications and source records attributed to Jin, B..

At least 19 recordsLinked to original sources

Assessing fish biodiversity and community structure in the Ganjiang River using eDNA metabarcoding

Hydropower development has emerged as a major driver of global environmental change, causing significant ecological damage to freshwater ecosystems and threatening aquatic biodiversity. However, the impact of cascade dams on fish communities in large river systems remains poorly understood, particularly in biodiversity hotspots such as China. Here, we used environmental DNA (eDNA) metabarcoding to assess the spatiotemporal patterns of fish diversity and community structure in the Ganjiang River, the largest tributary of the Yangtze River, in relation to cascade hydropower development. We collected water samples from 19 sites along the main stem and major tributaries in both wet and dry seasons, and analyzed the eDNA data using high-throughput sequencing and advanced bioinformatics pipelines. Our results revealed significant seasonal and spatial variations in fish diversity and community composition, with lower species richness and distinct assemblages in the impounded sections upstream of the dams compared to the downstream reaches. The fish communities were strongly influenced by environmental factors such as water temperature, pH, dissolved oxygen, and nutrients, which exhibited complex interactions with dam operation and land use practices. Spatial scale analyses further indicated that the impact of dams on fish diversity was most pronounced at the local scale, but also detectable at the regional scale. Our findings provide novel insights into the ecological consequences of cascade hydro-power development on fish communities and highlight the importance of considering spatial scales and environmental heterogeneity in assessing the impacts of human activities on freshwater biodiversity. Our study demonstrates the power of eDNA metabarcoding as a cost-effective and non-invasive tool for biodiversity assessment and conservation planning in large river systems facing multiple stressors and knowledge gaps.

ecology↗

Profiling of Aggregated Amyloid β42-induced Proteomic Alterations in KOLF2.1J Induced Pluripotent Stem Cell-derived Neurons

Amyloid[beta]; (A[beta];) plaques are a hallmark of Alzheimer[prime]s disease (AD). A human cellular neuronal model that recaptures A[beta];-induced pathology is critical for advancing AD research. However, comprehensive proteomic profiling of A[beta];-induced cellular model remains elusive. In this study, we investigated the proteomic changes in induced pluripotent stem cell (iPSC)-derived neurons (iNs) exposed to synthetic A[beta]; (1-42) peptides (A[beta];42A) to improve our understanding of the cellular responses of A[beta]; aggregates and to establish a human-related platform for AD research. A[beta];42A formed extracellular aggregates around neuronal soma and neurites, impaired neurite outgrowth, and induced the expression of multiple AD-associated genes, such as APOE, BACE1, ADAM10. To define the molecular landscape of A[beta];-induced neuronal dysfunction, we performed proteomic analyses of whole-cell lysates as well as soma- and neurite-enriched fractions. Proteomic profiling revealed extensive gene alterations in pathways associated with synaptic function, neuronal maintenance, and AD pathogenesis, such as the upregulation of APOE. Importantly, the A[beta];42A-iNs system recapitulated molecular signatures observed in AD brain tissue and cerebrospinal fluid. Representative protein changes, including APOE upregulation and its colocalization with A[beta]; aggregates, were further validated in postmortem human AD brain tissue. Together, these findings manifest that the A[beta];42A-iNs system reproduces multiple cellular and molecular features of AD and exhibits strongly consensus with clinical observations. It provides a valuable platform for investigating A[beta];-driven neurodegeneration and for the discovery of therapeutic targets for AD.

neuroscience↗

Somatic mutations and single-nucleus transcriptomics reveal uniquely human properties of neuronal aging

Human brain aging is frequently studied in model mammals that rarely show the natural age-related neurodegenerative conditions that afflict humans, yet little is known about how genomic stability compares across species during aging. Although somatic single nucleotide variant (SNV) and short insertion/deletion (Indel) mutations accumulate at rates that inversely scale to lifespan in colon cells - leaving diverse mammals with similar end-of-life burdens of mutations - here we show that cerebral cortical neurons accumulate SNVs at annual rates that are remarkably similar across six mammalian species (human, chimpanzee, rhesus macaque, marmoset, ferret, mouse) resulting in >12-fold more mutations in human neurons at the end of life compared to mouse neurons. Despite the conservation of overall annual mutation accumulation rates, mutational patterns--and hence likely mutagenic mechanisms--show sharp differences between species, with a nucleotide substitution pattern linked to neurodegenerative diseases accumulating almost exclusively in humans during aging. Coinciding with their higher mutational burden, single-nucleus transcriptomic analyses reveal pervasive age-associated proteostasis and mitochondrial dysregulation in human neurons that is far less pronounced in aged chimpanzees and rhesus macaques. These findings show that the pervasive effects of human neuronal aging might be linked to our long lifespan and are therefore not evident in animal models.

neuroscience↗

ProtPipe2: Multi-Platform Downstream Proteomics Analysis Tool

Proteomics studies increasingly use different technologies, including mass spectrometry, the antibody-based Olink platform, and the aptamer-based SomaScan platform. However, downstream analysis often depends on platform-specific scripts or point-and-click tools, limits flexibility and makes analyses difficult to reuse across platforms. We developed ProtPipe2, a downstream proteomics analysis framework for mass spectrometry, Olink, and SomaScan data that is available as both an R package and an interactive web application. ProtPipe2 supports quality control, preprocessing, imputation, batch correction, statistical analysis, visualization, pathway analysis, and result export. ProtPipe2 expands the original Protpipe workflow to additional proteomics platforms and provides reusable R functions for imputation, batch correction, and other downstream analyses. Its redesigned web application provides user-controlled methods and parameters through the same R-based workflow. Case studies across mass spectrometry, Olink, and SomaScan datasets demonstrated a consistent downstream analysis workflow across platforms. By supporting three proteomics platforms through both graphical and scripted workflows, ProtPipe2 makes downstream analysis easier to perform, repeat, and review. ProtPipe2 is freely available at https://nih-card.github.io/ProtPipe2/.

bioinformatics↗

Physics-Driven Zero-Shot Reconstruction of Isotropic 3D Fluorescence Microscopy under Undersampled Acquisition

Three-dimensional (3D) imaging represents the development of next generation of fluorescence microscopy. However, routine axial down-sampling makes isotropic resolution unrealistic. Here, we propose DeepUI, a physical zero-shot framework designed to achieve isotropic 3D fluorescence images from a low axial sampling rate. DeepUI fully leverages the intrinsic characteristics of 3D images through physics-guided degradation, which incorporates spatial-frequency joint learning to generate a scaled optical transfer function, combined with noise degradation and an up-sampling branch. Typically requiring just 5 minutes for training and 0.5 minutes for high-throughput and fast prediction, we demonstrate the superior performance of DeepUI to get isotropic results, and the exclusivity to axial down-sampling conditions, even in more challenging conditions, including defocused background, noise, and resolution blur.

bioinformatics↗

The heat-ramp method to study regulated cell death in a pathogenic yeastCryptococcus neoformans

Human fungal pathogens cause a significant public health burden. While no reliable surveilence data are available, estimations suggest that 1 billion infections and over 2 million deaths are attributable to fungal infections annually worldwide. This drove the World Health Organization to generate a priority list of fungal pathogens for reearch, which includes the yeast Cryptococcus neoformans in a top critical priority. With the rise of drug-resistance and emerging fungal pathogens, new conceptual strategies for antifungal therapies are needed in addition to existing antibiotic development pipelines to meet clinical needs. Intrinsic cell death pathways encoded by pathogenic fungi are largely unstudied but could be leveraged for antifungal therapy analogous to anti-cancer therapeutics that activate apoptosis or other cell death mechanisms. Thus far, molecularly defined fungal cell death mechanisms are best characterized for only a few, predominantly model filamentous species. To extend these studies to pathogenic yeast, here we describe and demonstrate a tunable heat-ramp stimulus that when applied to small volumes of yeast cell suspensions reveals a protracted cell death process in the pathogenic yeast Cryptococcus neoformans. This low cost protocol induces robust and reproducible phenotypes to study gene-dependent mechanisms in laboratory strains and clinical isolates.

microbiology↗

A Population-scale Single-cell Spatial Transcriptomic Atlas of the Human Cortex

The genetic and spatial determinants of cell type diversity in human cerebral cortices remain poorly defined. Here, we present a population-level single-cell spatial transcriptomic atlas of human cortices from 71 donors across the lifespan. We identified 906 layer-specific genes showing conserved and divergent laminar expression patterns between humans and other species. Spatial analysis revealed neuronal vulnerability and glial activation during aging, together with a decline in the proportion of superficial SST neurons and their interactions with other cells. Disease-associated genes exhibited high cell-type and layer-specific expression, implicating the pathogenic role of spatially specific gene expression. Spatial cis-eQTL analysis identified regulatory variants linked to genes related to diseases like Tourette syndrome. Cross-species comparison demonstrated glial expansion in the human cortex, accompanied by enhanced neuron-glia communication via the neuregulin signaling. Together, we provide a comprehensive single-cell atlas of the human cortex that is essential for understanding aging, evolution, and disease pathogenesis.

neuroscience↗

Neurons accumulate disease-specific somatic genomic changes across taupathologic states in Alzheimer's disease

Tau deposition within neurons marks Alzheimers disease (AD) neuropathology, suggesting that tau may contribute to cellular dysfunction and death. In AD, somatic mutations accumulate in neurons, with features that suggest deleterious effects on cellular function. To examine the relationship between tau and somatic mutation, we isolated neurons according to tau pathology and performed single-cell whole-genome sequencing on tau+, tau-, and tau-agnostic neurons from 13 individuals with AD, as well as neurons from 15 control individuals. We found that AD neurons, regardless of tau status, exhibited an increased burden of somatic single-nucleotide variants (sSNVs) and insertions and deletions (sIndels). Mutational signature analyses revealed disease-specific patterns, including sIndels characterized by two-basepair (2bp) deletions, indicating shared mutagenic mechanisms in AD neurons across tau pathologic cell states. Somatic mutations are associated with tissue-wide tau pathology, suggesting that tangles do not confer cell-autonomous genotoxicity to neurons and that non-tangle components drive somatic mutation in AD.

genomics↗

Large-scale HLA immunopeptidome and interactome profiling in microglia

Microglia are immune cells of the brain and act as major antigen presenting cells. Antigen presentation involves the human leukocyte antigen (HLA) complex, which is implicated in genetic risk of multiple neurodegenerative diseases. How HLA affects the function of microglia in the context of neurodegenerative disease remains unclear. Here, we investigated the HLA epitopes and their protein interactome in human induced pluripotent stem cell (iPSC)-derived microglia-like cells (iMGLs) using systematic mass spectrometry (MS)-based immunopeptidomics, whole-cell proteomics, affinity purification, and prediction algorithms. Our results revealed the presence of almost 7,000 peptides presented by HLA class I and II within microglia. We further showed that the immunopeptidome landscapes of iPSCs, iMGLs and interferon-gamma (IFN{gamma}) stimulated iMGLs are all readily distinguishable. Furthermore, HLA interacts with different groups of proteins in iPSCs compared to iMGLs which involve proteins in immune response. Importantly, we detected 25 HLA epitopes derived from 15 genes associated with Alzheimers and related dementias such as Tau, PLD3 (Alzheimers disease), TDP-43, FUS (Frontotemporal dementia), and PARK7, VPS35 (Lewy Body dementia). We predicted 31 mutant epitopes derived from these ADRD genes that could be presented with strong interaction to HLA molecules. Along with these epitopes, we observed an enrichment of immune-related interaction proteins in microglia treated with IFN{gamma}. These results provide evidence that aggregated and mutated proteins can interact with HLA alleles and be presented on the cell surface by microglia cells. This study sheds light on the antigen presenting and adaptive immunity mechanism within the central nervous system and its possible effects on neurodegenerative diseases.

immunology↗

Harnessing the Power of Single-Cell Large Language Models with Parameter Efficient Fine-Tuning using scPEFT

Single-cell large language models (scLLMs) capture essential biological insights from vast single-cell atlases but struggle in out-of-context applications, where zero-shot predictions can be unreliable. To address this, we introduce a single-cell parameter-efficient fine-tuning (scPEFT) framework that integrates learnable, low-dimensional adapters into scLLMs. By freezing the backbone model and updating only the adapter parameters, scPEFT efficiently adapts to specific tasks using limited custom data. This approach mitigates catastrophic forgetting, reduces parameter tuning by over 96%, and decreases GPU memory usage by more than half, significantly enhancing scLLMss accessibility for resource-constrained researchers. Validated across diverse datasets, scPEFT outperformed zero-shot models and traditional fine-tuning in disease-specific, cross-species, and under-characterized cell population tasks. Its attention-mechanism analysis identified COVID-related genes associated with specific cell states and uncovered unique blood cell subpopulations, demonstrating scPEFTs capacity for condition-specific interpretations. These findings position scPEFT as an efficient solution for improving scLLMs utilities in general single-cell analyses.

cell biology↗

Temporal dynamics of proteome and phosphorproteome during neuronal differentiation in the reference KOLF2.1J iPSC line

Induced pluripotent stem cell (iPSC)-derived neurons have emerged as a powerful model to investigate both neuronal development and neurodegenerative diseases. Although transcriptomics and imaging have been applied to characterize neuronal development signatures, comprehensive datasets of protein and post-translational modifications (PTMs) are not readily available. Here, we applied quantitative proteomics and phosphoproteomics to profile the differentiation of the KOLF2.1J iPSC line, the first reference line of the iPSC Neurodegenerative Disease Initiative (iNDI) project. We developed an automated workflow enabling high-coverage enrichment of proteins and phosphoproteins. Our results revealed molecular signatures across proteomic and phosphoproteomic landscapes during differentiation of iPSC-derived neurons. Proteomic data highlighted distinct changes in mitochondrial pathways throughout the course of differentiation, while phosphoproteomics revealed specific regulatory dynamics in GTPase signaling pathways and microtubule proteins. Additionally, phosphosite dynamics exhibited discordant trends compared to protein expression, particularly in processes related to axon functions and RNA transport. Furthermore, we mapped the kinase dynamic changes that are critical for neuronal development and maturation. We developed an interactive Web app (https://niacard.shinyapps.io/Phosphoproteome/) to visualize temporal landscape dynamics of protein and phosphosite expression. By establishing baselines of proteomic and phosphoproteomic profiles for neuronal differentiation, this dataset offers a valuable resource for future research into neuronal development and neurodegenerative diseases using this reference iPSC line. HighlightsO_LITemporal dynamics of proteome and phosphoproteome profiles in KOLF2.1J iPSC derived neurons. C_LIO_LIPhosphoproteomics highlights GTPase signaling and microtubule regulation in neuronal differentiation. C_LIO_LIKinome mapping reveals a shift in kinase activity patterns from early to late differentiation. C_LIO_LIShinyapp for visualizing the trajectory of protein and phosphosite expression during neuronal differentiation. C_LI

neuroscience↗

Single-cell spatial transcriptome reveals pathological features of human hippocampus with sclerosis

More than half of epileptic patients ultimately turned to intractable epilepsy. Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS), the most common type of intractable epilepsies, whose pathological mechanism remains elusive. Here, using 42 human hippocampal samples from surgical donors of MTLE (32 with and 10 without HS) through single-cell resolution Stereo-seq and histologcial experiments, we revealed spatially pathological changes of gene expression and cell type composition with HS systematically. After precise parcellation of hippocampal subregions and differentially expressed gene (DEG) analysis between each region with and without sclerosis, we found Cornu Ammonis (CA) subregions with higher number of DEGs were vulnerable to sclerosis, especially CA1 and CA3. Within CA1, we found that CA1-superficial and proximal areas were more vulnerable than CA1-deep and distal areas in sclerosis. Meanwhile, after analyzing 350,795 segmented cells from Stereo-seq, we found dramatically increasing density of astrocyte accompanied with significantly decreasing density of excitatory neurons in CA1, especially superficial and proximal CA1, and CA3 in sclerosis. In these two vulnerable subregions, proliferative astrocyte (P_astrocyte) and reactive astrocyte (R_astrocyte) were found to be enriched whereas apoptotic subtype of astrocyte (A_astrocyte), related with apoptotic pathway, was mainly located in alveus, which strengthened cell communication with reactive microglia (R_microglia) in HS, revealing the novel pathological feature in our work. The pseudotime analysis indicated that CA excitatory neurons underwent synaptic impairment, energy dysfunction, aging, and finally losing cell identity until death through autophagy or apoptosis. Besides, we also found a resilient subtype, EX_CA2-4.3, highly expressed extracellular matrix related genes including PDYN, and was increasing the interaction of BDNF-NTRK, NFASC-CNTN1 to withstand the damage from sclerosis. Together, our study provided a reference of human hippocampus with and without HS caused by MTLE, and highlighted the potential pathological mechanism on molecular and cellular level of MTLE-HS.

neuroscience↗

Apolipoprotein E ε4 exacerbates microglia-mediated complement-dependent synapse loss caused by neuronal Tpk deficiency

Thiamine pyrophosphokinse-1 (TPK) is a key enzyme that converts thiamine to functional thiamine diphosphate (TDP). TPK insufficiency and hence TDP reduction in neurons induced by amyloid-{beta} deposition and diabetes, an independent risk factor of Alzheimers disease (AD), recapitulate multi-pathophysiological features in the brain of mice, similar to those in human AD. Apolipoprotein E {varepsilon}4 allele (APOE4) is the most well-known genetic risk factor for AD. Clinical trials by boosting TDP using benfotiamine, a derivative of thiamine that significantly elevates TDP level in human encrythrocytes, have shown the inferior clinical efficacies in APOE4 carriers compared to non-APOE4 carriers. Clarifying the relationship between APOE4 and TPK expression and multi-pathophysiological characteristics of AD induced by Tpk deficiency in neurons is imperative. Here, we find that humanized APOE4 didnt directly affect Tpk expression of mice, but markedly aggravates behavior abnormalities of Tpk-cKO mice. Pathologically, the Tpk-cKO mice with humanized APOE4 knock-in (AE-cKO mice) exhibit more synapse loss than the mice with only humanized APOE4 knock-in and the Tpk-cKO mice. Transcriptomics and pathologic analysis identified that APOE4 promoted the overactivation of microglia and the transition of microglia to a disease-associated and phagocytosis state via a complement-mediated pathway. Further, the C3aR antagonist significantly repressed microglia phagocytosis and synaptic elimination of the AE-cKO mice. Our results demonstrate that APOE4 exacerbates behavior dysfunction of Tpk-cKO mice through microglia-mediated complement-dependent synaptic elimination. These findings provide important insights into the role of APOE4 in the pathogenesis of AD.

neuroscience↗

Glycerol-3-phosphate activates ChREBP, FGF21 transcription and lipogenesis in Citrin Deficiency

Citrin Deficiency (CD) is caused by inactivation of SLC25A13, a mitochondrial membrane protein required to move electrons from cytosolic NADH to the mitochondrial matrix in hepatocytes. People with CD do not like sweets. We discovered that SLC25A13 loss causes accumulation of glycerol-3-phosphate (G3P), which activates carbohydrate response element binding protein (ChREBP) to transcribe FGF21, which acts in the brain to restrain intake of sweets and alcohol, and to transcribe key genes of de novo lipogenesis. Mouse and human data establish G3P-ChREBP as a new mechanistic component of the Randle Cycle that contributes to metabolic dysfunction-associated steatotic liver disease (MASLD) and forms part of a system that communicates metabolic states from liver to brain in a manner that alters food and alcohol choices. The data provide a framework for understanding FGF21 induction in varied conditions, suggest ways to develop FGF21-inducing drugs, and drug candidates for both lean MASLD and support of urea cycle function in CD.

molecular biology↗

The conformational equilibria of a human GPCR compared between lipid vesicles and aqueous solutions by integrative 19F-NMR

Endogenous phospholipids influence the conformational equilibria of G protein-coupled receptors, regulating their ability to bind drugs and form signaling complexes. However, most studies of GPCR-lipid interactions have been carried out in mixed micelles or lipid nanodiscs. Though useful, these membrane mimetics do not fully replicate the physical properties of native cellular membranes associated with large assemblies of lipids. We investigated the conformational equilibria of the human A2A adenosine receptor (A2AAR) in phospholipid vesicles using 19F solid-state magic angle spinning NMR (SSNMR). By applying an optimized sample preparation workflow and experimental conditions, we were able to obtain 19F-SSNMR spectra for both antagonist- and agonist-bound complexes with sensitivity and linewidths closely comparable to those achieved using solution NMR. This facilitated a direct comparison of the A2AAR conformational equilibria across detergent micelle, lipid nanodisc, and lipid vesicle preparations. While antagonist-bound A2AAR showed a similar conformational equilibria across all membrane and membrane mimetic systems, the conformational equilibria of agonist-bound A2AAR exhibited differences among different environments. This suggests that the conformational equilibria of GPCRs may be influenced not only by specific receptor-lipid interactions but also by the membrane properties found in larger lipid assemblies.

biophysics↗

BTFBS: binding-prediction of bacterial transcription factors and binding sites based on deep learning

BackgroundThe binding of transcription factors (TFs) to TF-binding sites plays a vital role in the process of regulating gene expression and evolution. With the development of machine learning and deep learning, some successes have been achieved in predicting transcription factors and binding sites. Then a natural question arises: for a given transcription factor and a binding site, do they bind? This is the main motivation of this work. ResultsIn this paper, we develop a model BTFBS, which predicts whether the bacterial transcription factors and binding sites combine or not. The model takes both the amino acid sequences of bacterial transcription factors and the nucleotide sequences of binding sites as inputs, and extracts features through convolutional neural network and MultiheadAttention. For the model inputs, we use two negative sample sampling methods: RS and EE. On the test dataset of RS, the accuracy, sensitivity, specificity, F1-score and MCC of BTFBS are 0.91446, 0.89746, 0.93134, 0.91264 and 0.82946, respectively. And on the test dataset of EE, the accuracy, sensitivity, specificity, F1-score and MCC of BTFBS are 0.87868, 0.89354, 0.86394, 0.87996 and 0.75796, respectively. Meanwhile, our findings indicate that the optimal approach for obtaining negative samples in the context of bacterial research is to utilize the whole genome sequences of the corresponding bacteria, as opposed to the shuffling method. ConclusionsThe above results on the test dataset have shown that the proposed BTFBS model has a good performance in predicting the combination of bacterial transcription factors and their binding sites and provides an experimental guide. BTFBS is publicly available at https://github.com/Vceternal/BTFBS.

bioinformatics↗

The mechanism and consequences of amyloid-β modulating thiamine pyrophosphokinase-1 expression in microglia

Ample studies attribute cognitive decline in Alzheimers disease to amyloid-{beta} deposition 1-6. However, brain amyloid-{beta} accumulation that saturates years before the manifestation of clinical symptoms is dissociated with cognitive decline of the disease 7. It is unknown how these two processes are mechanistically linked. In this and our accompanied study, we report that thiamine pyrophosphokinase-1 (TPK) deficiency plays essential roles in both processes via distinct mechanisms. Here we describe that diminished microglia Tpk controls the propagation of amyloid-{beta} plaques. In APP/PS1 transgenic mice, microglia showed elevated Tpk expression at 2-month-old, but reduction in a plaque-centric manner at 8-month-old. Interestingly, lipopolysaccharide, but not amyloid-{beta}, induceed Tpk reduction in cultured microglia. Tpk reduction led to microglia dysfunction, showing volatile motility but reduced phagocytosis and weak response to focal tissue injury, with accumulation of intracellular lipid droplets and abnormal mitochrondria. In Alzheimers disease mice, microglia-specific knockout of Tpk caused diminished plaque coverage, exacerbated plaque burden and synaptic loss. However, increased plaques were not accompanied by the development of neurofibrillary tangles or brain atrophy, in contrast to the phenotype described in our accompanied paper with neuronal Tpk deletion. In conclusion, plaque-induced inflammation reduces Tpk in microglia, selectively exacerbating the spread of amyloid pathology.

neuroscience↗

Negative Selection Allows DNA Mismatch Repair-Deficient Mouse Fibroblasts In Vitro to Tolerate High Levels of Somatic Mutations

Substantial numbers of somatic mutations have been found to accumulate with age in different human tissues. Clonal cellular amplification of some of these mutations can cause cancer and other diseases. However, it is as yet unclear if and to what extent an increased burden of random mutations can affect cellular function without clonal amplification. We tested this in cell culture, which avoids the limitation that an increased mutation burden in vivo typically leads to cancer. We performed single-cell whole-genome sequencing of primary fibroblasts from DNA mismatch repair (MMR) deficient Msh2-/- mice and littermate control animals after long-term passaging. Apart from analyzing somatic mutation burden we analyzed clonality, mutational signatures, and hotspots in the genome, characterizing the complete landscape of somatic mutagenesis in normal and MMR-deficient mouse primary fibroblasts during passaging. While growth rate of Msh2-/-fibroblasts was not significantly different from the controls, the number of de novo single-nucleotide variants (SNVs) increased linearly up until at least 30,000 SNVs per cell, with the frequency of small insertions and deletions (INDELs) plateauing in the Msh2-/- fibroblasts to about 10,000 INDELS per cell. We provide evidence for negative selection and large-scale mutation-driven population changes, including significant clonal expansion of preexisting mutations and widespread cell-strain-specific hotspots. Overall, our results provide evidence that increased somatic mutation burden drives significant cell evolutionary changes in a dynamic cell culture system without significant effects on growth. Since similar selection processes against mutations preventing organ and tissue dysfunction during aging are difficult to envision, these results suggest that increased somatic mutation burden can play a causal role in aging and diseases other than cancer.

genomics↗