Biology subjects

Wang, B.

Publications and source records attributed to Wang, B..

At least 343 records · Page 19Linked to original sources

bioRxiv2023

Machine learning-based revelation of GABBR1 and IQGAP2 as candidate biomarkers of pulmonary arterial hypertension and their correlation with immune infiltration

Pulmonary arterial hypertension (PAH) is a pulmonary vascular disease with complex pathogenesis, and its intrinsic molecular mechanisms remain unclear. The aim of this study was to screen gene expression data from PAH patients, identify possible diagnostic indicators of PAH and to investigate the role of immune cell infiltration in the progression of PAH. This study made use of the gene expression dataset of PAH patients from the GEO database. R software was used to identify differentially expressed genes and perform functional enrichment analysis. The SVM-RFE, LASSO and Random Forest algorithms were then used to screen for PAH hub genes and validated in the peripheral blood and lung tissue datasets. Finally, the CIBERSORT algorithm was used to assess PAH lung tissue immune cell infiltration and to investigate the correlation between hub genes and immune cells. A total of 132 DEGs were screened in this study, which were centrally involved in the neuroreceptor-ligand activity pathway and associated with neurotransmission and hemoglobin complex. A total of 2 pivotal genes, GABBR1 and IQGAP2, were obtained by machine learning algorithms. The 2 pivotal genes had good predictive power as verified by ROC curves. Further immune infiltration analysis showed a decrease in T cells and an increase in the proportion of macrophages and dendritic cells in the lung tissue of PAH patients. The expression of GABBR1 was positively correlated with T cells and negatively correlated with macrophages and dendritic cells. In our study, we identified 2 potential diagnostic key genes: GABBR1 and IQGAP2. Our findings may provide a theoretical basis for the analysis of the underlying mechanisms of PAH and the development of targeted medicines. Highlight BoxO_ST_ABSKey findingsC_ST_ABSO_LIWe identified 2 potential key genes of PAH, GABBR1 and IQGAP2. C_LI What is known and what is new?O_LISympathetic hyperexcitability as well as immune responses are closely associated with the development of PAH, and pulmonary vascular hyperplasia is a key pathogenetic mechanism of PAH. C_LIO_LIImportant biomarkers related to neuroreceptors and immune responses in PAH lung tissue have not been identified, while our study identified GABBR1 as a key neuroreceptor and immune cell regulator in PAH. IQGAP2 could be a new hotspot direction for pulmonary vascular remodeling. C_LI What is the implication, and what should change now?O_LIGABBR1 and IQGAP2 may be potential therapeutic targets for PAH. The new horizon provided by this study will provide some reference for subsequent PAH studies. C_LI

bioinformatics↗

bioRxiv2023

Evaluation of normalization methods for predicting quantitative phenotypes in metagenomic data analysis

Significant advancements have been made in metagenomic research for the prediction of phenotypes based on microbiome data. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field holds great promise in revealing intricate connections between microbial communities and host health. However, the presence of heterogeneity in microbiome datasets poses a substantial challenge to the accuracy of predictions and undermines the reproducibility of models. To tackle this challenge, we investigated 22 normalization methods aimed at removing heterogeneity across multiple datasets, conducted a comprehensive review of them, and evaluated their effectiveness in predicting quantitative phenotypes using 3 simulations and 31 real datasets. The results indicate that none of these methods demonstrate significant superiority in predicting quantitative phenotypes or attain a noteworthy reduction in root mean squared error of the predictions. Given the frequent occurrence of batch effects and the satisfactory performance of batch correction methods in predicting datasets affected by these effects, we strongly recommend utilizing batch correction methods as the initial step in predicting quantitative phenotypes. In summary, the performance of normalization methods in predicting metagenomic data remains a dynamic and ongoing research area. Our study contributes to this field by undertaking a comprehensive evaluation of diverse methods and offering valuable insights into their effectiveness in predicting quantitative phenotypes.

bioinformatics↗

bioRxiv2023

Pharmacologically inducing regenerative cardiac cells by small molecule drugs

Adult mammals, unlike some lower organisms, lack the ability to regenerate damaged hearts through cardiomyocytes (CMs) dedifferentiation into cells with regenerative capacity. Developing conditions to induce such naturally unavailable cells with potential to proliferate and differentiate into CMs, i.e., regenerative cardiac cells (RCCs), in mammals will provide new insights and tools for heart regeneration research. In this study, we demonstrate that a two-compound combination, CHIR99021 and A-485 (2C), effectively induces RCCs from human embryonic stem cell (hESC)-derived TNNT2+ CMs in vitro, as evidenced by lineage tracing experiments. Functional analysis shows that these RCCs express a broad spectrum of cardiogenesis genes and have the potential to differentiate into functional CMs, endothelial cells (ECs), and smooth muscle cells (SMCs). Importantly, similar results were observed in neonatal rat CMs both in vitro and in vivo. Remarkably, administering 2C in adult mouse hearts significantly enhances survival and improves heart function post-myocardial infarction. Mechanistically, CHIR99021 is crucial for the transcriptional and epigenetic activation of genes essential for RCC development, while A-485 primarily suppresses H3K27Ac and particularly H3K9Ac in CMs. Their synergistic effect enhances these modifications on RCC genes, facilitating the transition from CMs to RCCs. Therefore, our findings demonstrate the feasibility and reveal the mechanisms of pharmacological induction of RCCs from endogenous CMs, which could offer a promising regenerative strategy to repair injured hearts.

cell biology↗

bioRxiv2023

Epigenome erosion in Alzheimer's disease brain cells and induced neurons

Late-onset Alzheimers disease (LOAD) is typically sporadic, correlated only to advanced age, and has no clear genetic risk factors. The sporadic nature of LOAD presents a challenge to understanding its pathogenesis and mechanisms. Here, we comprehensively investigated the epigenome of LOAD primary entorhinal cortex brain tissues via single-cell multi-omics technologies, simultaneously capturing DNA methylation and 3D chromatin conformation. We identified AD-specific DNA methylation signatures and found they interact with bivalent promoters of AD differentially expressed genes. In addition, we discovered global chromosomal epigenome erosion of 3D genome structure within and across brain cell types. Furthermore, to evaluate whether these age- and disease-dependent molecular signatures could be detected in the in vitro cellular models, we derived induced neurons (iNs) converted directly from AD patients fibroblasts and found a set of conserved methylation signatures and shared molecular processes. We developed a machine-learning algorithm to identify robust and consistent methylation signatures of LOAD in vivo primary brain tissues and in vitro fibroblast-derived iNs. The results recapitulate the age- and disease-related epigenetic features in iNs and highlight the power of epigenome and chromatin conformation for identifying molecular mechanisms of neuronal aging and generating biomarkers for LOAD. HIGHLIGHTO_LIAD-specific DNA methylation signatures are identified in entorhinal cortex brain cell types C_LIO_LIThe AD differentially expressed genes linked with differentially methylated regions via loop interactions are enriched in a bivalent chromatin state C_LIO_LIChromosomal epigenome erosion of 3D genome structures occurs in LOAD brain cell types. C_LIO_LIShared and reliable methylation signatures are observed in both in vitro cellular iN models and primary brain tissues. C_LIO_LIMachine learning models identify robust and reliable methylation loci as AD biomarkers across cell types. C_LI

genomics↗

bioRxiv2023

Comparison of the effectiveness of different normalization methods for metagenomic cross-study phenotype prediction under heterogeneity

The human microbiome, comprising microorganisms residing within and on the human body, plays a crucial role in various physiological processes and has been linked to numerous diseases. To analyze microbiome data, it is essential to account for inherent heterogeneity and variability across samples. Normalization methods have been proposed to mitigate these variations and enhance comparability. However, the performance of these methods in predicting binary phenotypes remains understudied. This study systematically evaluates different normalization methods in microbiome data analysis and their impact on disease prediction. Our findings highlight the strengths and limitations of scaling, compositional data analysis, transformation, and batch correction methods. Scaling methods like TMM and RLE show consistent performance, while compositional data analysis methods exhibit mixed results. Transformation methods, such as Blom and NPN, demonstrate promise in capturing complex associations. Batch correction methods, including BMC and Limma, consistently outperform other approaches. However, the influence of normalization methods is constrained by population effects, disease effects, and batch effects. These results provide insights for selecting appropriate normalization approaches in microbiome research, improving predictive models, and advancing personalized medicine. Future research should explore larger and more diverse datasets and develop tailored normalization strategies for microbiome data analysis.

bioinformatics↗

bioRxiv2023

Regulated Cleavage and Relocation of FERONIA Control Immunity in Arabidopsis Roots

Plant roots exhibit localized immunity (LI) specifically in the root cap and transition/elongation zone (TZ/EZ). Such immunity relies on receptor-like kinases localized at the plasma membrane (PM), which are essential for plant response to bacteria in the rhizosphere. Here, we identified a new mechanism of action for receptor kinase FERONIA (FER) in LI. In the absence of bacterial stimuli, FER is localized to the PM, maintaining plant growth. When confronted with bacterial colonization, RALF23 peptide hyper-accumulates in TZ/EZ cells and activates a metalloproteinase that cleaves FER and transfer the cytosolic kinase domain into the nucleus. The nucleus-localized kinase domain of FER contributes to LI by reducing bacterial abundance at TZ/EZ. Thus, this work uncovered a unique mechanism by which a single receptor kinase acts in two molecular forms and two distinct subcellular locations to balance growth and immunity. One Sentence SummaryBacteria induces the cleavage of FER via At2-MMP to trigger a localized immunity around TZ and EZ of Arabidopsis roots.

plant biology↗

bioRxiv2023

Climate warming suppresses soil abundant fungal taxa and reduces soil carbon efflux in a semi-arid grassland

The abundance, diversity and activity of soil microorganisms critically control the fate of recent plant carbon (C) inputs as well as protecting soil organic C, regulating C-climate feedbacks. However, the effects of climate change drivers such as warming and precipitation change on soil microbial communities and C dynamics remain poorly understood. Utilizing a long-term field warming and precipitation manipulation in a semi-arid grassland on the Loess Plateau and a complementary incubation experiment, here we show that warming and rainfall reduction differentially affect the abundance and composition of bacteria and fungi, and soil C efflux. Warming significantly reduced the abundance of fungi but not bacteria, increasing the relative dominance of bacteria in the soil microbial community. In particular, warming shifted the community composition of abundant fungi in favor of oligotrophic Capnodiales and Hypocreales over potential saprotroph Archaeorhizomycetales. In contrast, precipitation reduction increased soil microbial biomass, but did not significantly affect either the abundance or diversity of bacteria. Furthermore, soil abundant, not rare, fungal community composition was significantly correlated with soil CO2 efflux. Our findings suggest that alterations in the fungal community composition, in response to changes in soil C and moisture, dominate the microbial responses to climate change and thus control soil C dynamics in semi-arid grasslands. Impact statementSemi-arid grasslands play a critical role in global carbon (C) cycle and potential feedbacks to climate change. Understanding the responses of soil microorganisms to warming and rainfall change is key to evaluating and predicting semi-arid grassland soil C dynamics under future climate change scenarios. Our study showed that warming induced a shift in the abundant fungal community, favoring oligotrophic fungi (i.e., Capnodiales and Hypocreales) over the potential saprotrophic Archaeorhizomycetales, and reduced C efflux. These findings advance our understanding of soil microbial and C responses to climate change drivers and may help predict and possibly manage soil C sequestration in semi-arid grasslands.

ecology↗

bioRxiv2023

The SAM Domain of EphA2 Inhibits Ligand-Independent Clustering and Activation

Eph receptors are the largest family of receptor tyrosine kinases (RTKs). They play a role in the pathogenesis of various diseases including cancer, atherosclerosis, fibrosis, infectious diseases, diseases of the central nervous system and age-related cataract. EphA2 has attracted much attention over the years owing to its dysregulation in many diseases. Previous studies have revealed the unique molecular organizations of Eph receptors, and particularly EphA2, into large clusters of receptor-ligand complexes. One unique feature of Eph receptors is a C-terminal sterile alpha motif (SAM) domain, which has been proposed to alter dimerization and kinase activity in EphA2. However, the precise role of the SAM domain in regulating the function and oligomerization state of EphA2 has not been reported. Here we apply a time-resolve fluorescence spectroscopy, PIE-FCCS, to characterize the oligomerization state of EphA2 in live cells and determine the role of the SAM domain. We deleted the SAM domain in the context of full length EphA2 and an intracellular domain (ICD) construct to assess the effect of the SAM domain on oligomerization state, kinase activity, and cellular behavior. Overall, we find that the SAM domain inhibits ligand-independent clustering and kinase activity in both full-length EphA2 and the isolated ICD construct at the cell membrane. These results are consistent with the autoinhibitory features of the C-terminal tail of EGFR and may help resolve the allosteric regulation of other RTKs.

biophysics↗

bioRxiv2023

Light-induced trapping of endogenous proteins reveals spatiotemporal roles of microtubule and kinesin-1 in dendrite patterning of Drosophila sensory neurons

Animal development involves numerous molecular events, whose spatiotemporal properties largely determine the biological outcomes. Conventional methods for studying gene function lack the necessary spatiotemporal resolution for precise dissection of developmental mechanisms. Optogenetic approaches are powerful alternatives, but most existing tools rely on exogenous designer proteins that produce narrow outputs and cannot be applied to diverse or endogenous proteins. To address this limitation, we developed OptoTrap, a light-inducible protein trapping system that allows manipulation of endogenous proteins tagged with GFP or split GFP. This system turns on fast and is reversible in minutes or hours. We generated OptoTrap variants optimized for neurons and epithelial cells and demonstrate effective trapping of endogenous proteins of diverse sizes, subcellular locations, and functions. Furthermore, OptoTrap allowed us to instantly disrupt microtubules and inhibit the kinesin-1 motor in specific dendritic branches of Drosophila sensory neurons. Using OptoTrap, we obtained direct evidence that microtubules support the growth of highly dynamic dendrites. Similarly, targeted manipulation of Kinesin heavy chain revealed differential spatiotemporal requirements of kinesin-1 in the patterning of low- and high-order dendritic branches, suggesting that different cargos are needed for the growth of these branches. OptoTrap allows for precise manipulation of endogenous proteins in a spatiotemporal manner and thus holds great promise for studying developmental mechanisms in a wide range of cell types and developmental stages.

developmental biology↗

bioRxiv2023

Divergent Molecular Pathways for Toxicity of Selected Mutant C9ORF72-derived Dipeptide Repeats

Expansion of a hexanucleotide repeat in a noncoding region of the C9ORF72 gene is responsible for a significant fraction of Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD) cases, but mechanisms linking mutant gene products to neuronal toxicity remain debatable. Pathogenesis was proposed to involve the production of toxic RNA species and/or accumulation of toxic dipeptide repeats (DPRs) but distinguishing between these mechanisms has been challenging. In this study, we first use complementary model systems for analyzing pathogenesis in adult-onset neurodegenerative diseases to characterize the pathogenicity of DPRs produced by Repeat Associated Non-ATG translation of C9ORF72 in specific cellular compartments: isolated axoplasm and giant synapse from the squid. Results showed selective axonal and presynaptic toxicity of GP-DPRs, independent of associated RNA. These effects involved a MAPK signaling pathway that affects fast axonal transport and synaptic function, a pathogenic mechanism shared with other mutant proteins associated with familial ALS, like SOD1 and FUS. In primary cultured neurons, GP but not other DPRs promote the "dying-back" axonopathy seen in ALS. Interestingly, GR- and PR-DPRs, which had no effect on axonal transport or synaptic transmission, were found to disrupt the nuclear membrane, promoting "dying-forward" neuropathy. All C9-DPR-mediated toxic effects observed in these studies are independent of whether the corresponding mRNAs contained hexanucleotide repeats or alternative codons. Finally, C9ORF72 human tissues confirmed a close association between GP and active P38 in degenerating motor neurons as well as GR-associated nuclear damage in the cortex. Collectively, our studies establish compartment-specific toxic effects of C9-DPRs associated with degeneration, suggesting that two independent pathogenic mechanisms may contribute to disease heterogeneity and/or synergize on disease progression in C9ORF72 patients with ALS and/or FTD symptoms. Graphical AbstractActivation of protein kinases and inhibition of axonal transport, synaptic transmission, and nuclear structure are toxic effects common to unrelated FALS-related gene products. FALS-related mutant forms of SOD1 (mSOD1), FUS (mFUS), and C9-GP-DPRs (GP(n)) activate specific ASK1-MAPK pathway. Within axons, active ASK1-p38 pathway phosphorylates various substrates, including conventional kinesin, leading to the inhibition of fast axonal transport mediated by the translocation of this motor protein along microtubules. ASK1 can also inhibit synaptic transmission via JNK activation. Both pathways cause reductions in the availability of critical synaptic cargoes, synaptic dysfunction, and "dying-back" degeneration of neurons. On the other hand, C9- PR and GR-DPRs (PR(n) and GR(n)) activate other pathways, leading to aberrant alterations in nuclear structure and function and "dying-forward" degeneration of neurons, consistent with reports of transcriptional changes and activation of apoptosis in ALS. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/558663v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@162cbbeorg.highwire.dtl.DTLVardef@12e54caorg.highwire.dtl.DTLVardef@c0cdaborg.highwire.dtl.DTLVardef@1feb8d0_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Prothoracicotropic hormone controls female sexual receptivity through the function of ecdysone in pC1 neurons of Drosophila

Female sexual receptivity is essential for reproduction of a species. Neuropeptides play the main role in regulating female receptivity. However, whether neuropeptides regulate female sexual receptivity during the neurodevelopment is unknown. Here we found the peptide hormone prothoracicotropic hormone (PTTH), which belongs to the insect PG axis, negatively regulated virgin female receptivity through ecdysone during neurodevelopment in Drosophila melanogaster. We identified PTTH neurons as doublesex-positive neurons, they regulated virgin female receptivity before the metamorphosis during the 3rd-instar larval stage. PTTH deletion resulted in the increased EcR-A expression in the whole newly formed prepupae. Furthermore, the ecdysone receptor EcR-A in pC1 neurons positively regulated virgin female receptivity during metamorphosis. The decreased EcR-A in pC1 neurons induced abnormal morphological development of pC1 neurons without changing neural activity. Among all subtypes of pC1 neurons, the function of EcR-A in pC1b neurons was necessary for virgin female copulation rate. These suggested that the changes of synaptic connections between pC1b and other neurons decreased female copulation rate. Moreover, female receptivity significantly decreased when the expression of PTTH receptor Torso was reduced in pC1 neurons. This suggested that PTTH not only regulates female receptivity through ecdysone but also through affecting female receptivity associated neurons directly. The PG axis has similar functional strategy as the HPG axis in mammals to trigger the juvenile-adult transition. Our work suggests a general mechanism underlying which the neurodevelopment during maturation regulates female sexual receptivity.

neuroscience↗

bioRxiv2023

Quantitative Profiling of Lysosomal pH Heterogeneity using Fluorescence Lifetime Imaging Microscopy

Lysosomes play crucial roles in maintaining cellular homeostasis and promoting organism fitness. The pH of lysosomes is a crucial parameter for their proper function, and it is dynamically influenced by both intracellular and environmental factors. Here, we present a method based on fluorescence lifetime imaging microscopy (FLIM) for quantitatively analyzing lysosomal pH profiles in diverse types of primary mammalian cells and in different tissues of the live organism Caenorhabditis elegans. This FLIM-based method exhibits high sensitivity in resolving subtle pH differences, thereby revealing the heterogeneity of the lysosomal population within a cell and between cell types. The method enables rapid measurement of lysosomal pH changes in response to various environmental stimuli. Furthermore, the FLIM measurement of pH-sensitive dyes circumvents the need for transgenic reporters and mitigates potential confounding factors associated with varying dye concentrations or excitation light intensity. This FLIM approach offers absolute quantification of lysosomal pH and highlights the significance of lysosomal pH heterogeneity and dynamics, providing a valuable tool for studying lysosomal functions and their regulation in various physiological and pathological contexts.

cell biology↗

bioRxiv2023

Tissue-specific knockout in Drosophila neuromuscular system reveals ESCRT's role in formation of synapse-derived extracellular vesicles

Tissue-specific gene knockout by CRISPR/Cas9 is a powerful approach for characterizing gene functions in animal development. However, this approach has been successfully applied in only a small number of Drosophila tissues. The Drosophila motor nervous system is an excellent model system for studying the biology of neuromuscular junction (NMJ). To expand tissue-specific CRISPR to the Drosophila motor system, here we present a CRISPR-mediated tissue-restricted mutagenesis (CRISPR-TRiM) toolkit for knocking out genes in motoneurons, muscles, and glial cells. We validated the efficacy of this toolkit by knocking out known genes in each tissue, demonstrated its orthogonal use with the Gal4/UAS binary expression system, and showed simultaneous knockout of multiple redundant genes. Using these tools, we discovered an essential role for SNARE pathways in NMJ maintenance. Furthermore, we demonstrate that the canonical ESCRT pathway suppresses NMJ bouton growth by downregulating the retrograde Gbb signaling. Lastly, we found that axon termini of motoneurons rely on ESCRT-mediated intra-axonal membrane trafficking to lease extracellular vesicles at the NMJ. SIGNIFICANCE STATEMENTIn this study, we developed a tissue-specific Cas9 toolkit that enables gene knockout specifically in motor neurons, glial cells, and muscle cells, the three cell types of the Drosophila peripheral motor system. Complementary to existing RNAi methods, this versatile tissue-specific knockout system offers unique advantages for dissecting gene functions at the neuromuscular junction (NMJ). Using these tools, we discovered that SNARE-mediated secretory pathways are required to maintain the integrity of the NMJ and that ESCRT components play critical yet differential roles in the biogenesis of extracellular vesicles, bouton growth, and membrane turnover at the NMJ. This CRISPR toolkit can be applied to study many biological questions in the neuromuscular system.

neuroscience↗

bioRxiv2023

Deactivation of ligand-receptor interactions enhancing lymphocyte infiltration drives melanoma resistance to Immune Checkpoint Blockade

Immune checkpoint blockade (ICB) is a promising cancer therapy; however, resistance often develops. To learn more about ICB resistance mechanisms, we developed IRIS (Immunotherapy Resistance cell-cell Interaction Scanner), a machine learning model aimed at identifying candidate ligand-receptor interactions (LRI) that are likely to mediate ICB resistance in the tumor microenvironment (TME). We developed and applied IRIS to identify resistance-mediating cell-type-specific ligand-receptor interactions by analyzing deconvolved transcriptomics data of the five largest melanoma ICB therapy cohorts. This analysis identifies a set of specific ligand-receptor pairs that are deactivated as tumors develop resistance, which we refer to as resistance deactivated interactions (RDI). Quite strikingly, the activity of these RDIs in pre-treatment samples offers a markedly stronger predictive signal for ICB therapy response compared to those that are activated as tumors develop resistance. Their predictive accuracy surpasses the state-of-the-art published transcriptomics biomarker signatures across an array of melanoma ICB datasets. Many of these RDIs are involved in chemokine signaling. Indeed, we further validate on an independent large melanoma patient cohort that their activity is associated with CD8+ T cell infiltration and enriched in hot/brisk tumors. Taken together, this study presents a new strongly predictive ICB response biomarker signature, showing that following ICB treatment resistant tumors turn inhibit lymphocyte infiltration by deactivating specific key ligand-receptor interactions.

bioinformatics↗

bioRxiv2023

Volumetrically tracking retinal and choroidal structural changes in central serous chorioretinopathy

Central serous chorioretinopathy (CSCR) leads to accumulation of subretinal fluid and retinal thickness change, which can be readily detected in clinics using optical coherence tomography (OCT). However, current quantification methods usually require sophisticated processing such as retinal layer segmentations, and volumetric visualization of structural changes is generally challenging, which can hinder fast and accurate assessment of disease progression and/or treatment efficacy. In this study, we developed an algorithm that can register the OCT scans acquired from different visits without requiring prior layer segmentation and calculated the three-dimensional (3-D) structural change maps for patients with CSCR. Our results demonstrate that this tool can be useful in monitoring the progression of CSCR and revealing the resolution of pathologies following treatment automatically with minimal pre-processing.

bioengineering↗

bioRxiv2023

A hematopoietic stem cell subset that retains memory of prior inflammatory stress accumulates in aging and clonal hematopoiesis

Inflammation activates many blood cell types, driving aging and malignancy. Yet, hematopoietic stem cells (HSCs) survive a lifetime of infection to sustain life-long blood production. To understand HSC adaptation to inflammation, we developed xenograft inflammation-recovery models and performed single cell multiomics on isolated human HSC. Two transcriptionally and epigenetically distinct HSC subsets expressing canonical HSC programs were identified. Only one showed sustained transcriptional and epigenetic changes after recovery from inflammatory treatments. This HSC inflammatory memory (HSC-iM) program is enriched in memory T cells and HSCs from recovered COVID-19 patients. Importantly, HSC-iM accumulates with age and with clonal hematopoiesis. Overall, heritable molecular alterations in a subset of human HSCs, an adaptation to long-term inflammatory stress, may predispose to heightened age-related risk of blood cancer and infection. One-Sentence SummaryInflammation across a lifetime rewires human HSCs to produce a distinct HSC subset with both beneficial and deleterious fitness consequences.

cell biology↗

bioRxiv2023

Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

genetics↗

bioRxiv2023

The entire brain, more or less is at work: 'Language regions' are artefacts of averaging

Models of the neurobiology of language suggest that a small number of anatomically fixed brain regions are responsible for language functioning. This derives from centuries of aphasia studies and decades of neuroimaging. The latter rely on thresholded measures of central tendency applied to activity patterns from heterogeneous stimuli. We hypothesised that these methods obscure the whole brain distribution of regions supporting language. Specifically, language regions are connectivity hubs, coordinating varying peripheral activity that averages out following thresholding. We tested this with neuroimaging meta-analyses and movie-fMRI. Results show that words localise to language regions when averaged but are distributed throughout the brain when examining specific linguistic representations. These language regions are partially connectivity hubs that are spatiotemporally dynamic, making connections with [~]40% of the brain periphery outside those regions, and only appearing in the aggregate over time. Hub-periphery connections encode linguistic representations, not the language regions alone. Results replicate with audiobook-fMRI. Finally, intracranial neuronal recordings support findings, showing language regions are hub-like, with linguistic representations decodable throughout the brain. Together, these four studies suggest that language regions are artefacts of averaging heterogeneous language representations. Instead, they are connectivity hubs coordinating whole-brain distributed network representations, suggesting why their damage results in aphasia.

neuroscience↗