Biology subjects

Zhang, C.

Publications and source records attributed to Zhang, C..

At least 595 records · Page 33Linked to original sources

bioRxiv2023

Immune sensing of food allergens promotes aversive behaviour

In addition to its canonical function in protecting from pathogens, the immune system can also promote behavioural alterations1-3. The scope and mechanisms of behavioural modifications by the immune system are not yet well understood. Using a mouse food allergy model, here we show that allergic sensitization drives antigen-specific behavioural aversion. Allergen ingestion activates brain areas involved in the response to aversive stimuli, including the nucleus of tractus solitarius, parabrachial nucleus, and central amygdala. Food aversion requires IgE antibodies and mast cells but precedes the development of gut allergic inflammation. The ability of allergen-specific IgE and mast cells to promote aversion requires leukotrienes and growth and differentiation factor 15 (GDF15). In addition to allergen-induced aversion, we find that lipopolysaccharide-induced inflammation also resulted in IgE-dependent aversive behaviour. These findings thus point to antigen-specific behavioural modifications that likely evolved to promote niche selection to avoid unfavourable environments.

immunology↗

bioRxiv2023

Decomposing intraspecific phenotypic variation: implications for species and functional diversity

Researchers have a history of seeking explanation for and understanding of diversity patterns. High-dimensional trait-based trade-offs have been hypothesized as important for maintaining species and functional diversity. These relationships have primarily been investigated at the community-level, despite the importance of intraspecific variation to diversity maintenance. The goal of this research is to determine if alternative phenotypes are present within species and the impacts of this on diversity in a tropical seedling community in China. We ask 1) do trait combinations found across species, at the community-level, also exist within species?; 2) how consistent are alternative phenotypes and their contributions to growth across species?; and 3) how do findings align with species co-occurrence patterns? We model species-specific growth with individual-level trait measurements, environmental data, and their interactions, allowing for identification of intraspecific alternative phenotypes and quantification of the contribution of variables to growth. We find that two of three species have intraspecific alternative phenotypes. Specifically, individuals within these species share a trait combination, but how they combine the traits differs depending on the type and level of soil nutrients. Furthermore, we find that similarity among species in alternative phenotypes and variables that contribute most to growth may lead to negative spatial co-occurrence of species. Overall, we find that multiple traits or interactions between traits and the environment drive species-specific strategies for growth. These results highlight how individuals are highly variable, with phenotypically different individuals having similar growth performance, and suggest how high species and functional diversity can be maintained in communities.

ecology↗

bioRxiv2023

Analysis of skull thickness, scalp-to-cortex distance and association with age and sex in cognitively normal elderly

Personalized neurostimulation has been a potential treatment for many brain diseases, which requires insights into brain/skull geometry. Here, we developed an open source efficient pipeline BrainCalculator for automatically computing the skull thickness map, scalp-to-cortex distance (SCD), and brain volume based on T1-weighted magnetic resonance imaging (MRI) data. We examined the influence of age and sex cross-sectionally in 407 cognitively normal older adults (71.9{+/-}8.0 years, 60.2% female) from the ADNI. We demonstrated the compatibility of our pipeline with commonly used preprocessing packages and found that BrainSuite Skullfinder was better suited for such automatic analysis compared to FSL Brain Extraction Tool 2 and SPM12- based unified segmentation using ground truth. We found that the sphenoid bone and temporal bone were thinnest among the skull regions in both females and males. There was no increase in regional minimum skull thickness with age except in the female sphenoid bone. No sex difference in minimum skull thickness or SCD was observed. Positive correlations between age and SCD were observed, faster in females (0.307%/y) than males (0.216%/y) in temporal SCD. A negative correlation was observed between age and whole brain volume computed based on brain surface (females -1.031%/y, males -0.998%/y). In conclusion, we developed an automatic pipeline for MR-based skull thickness map, SCD, and brain volume analysis and demonstrated the sex-dependent association between minimum regional skull thickness, SCD and brain volume with age. This pipeline might be useful for personalized neurostimulation planning.

neuroscience↗

bioRxiv2023

Construction of Model Animals to Explore Intestinal Microbiome for Detection of Breast Cancer

Breast cancer ranks first among female cancers and has become a major public health problem in the current society. More studies indicated that these cancers are related to the change in the gut microbiome that can cause metabolic and immune system disorders in the body. However, there are few studies on the changes in gut microbiome caused by the onset of breast cancer, and the relationship between breast cancer and gut microbiome needs to be further clarified. In this study, we inoculated 4T1 breast cancer cells to induce breast cancer tumorigenesis in mice and collected their feces samples at different stages during this process. These intestinal florae were analyzed using 16S rRNA gene amplicon sequencing, and the results showed that at the phylum level, the ratio of Firmicutes/Bacteroidetes decreased with the development of the tumor; at the family level, the intestinal microbiome had obvious variations of Lachnospiraceae, Bacteroidaceae, Erysipelotrichaceae, etc. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and COG annotation demonstrated that decreased abundance of cancer related signaling pathways. This study elucidated the relationship between breast cancer and intestinal microbiome, and the research results can be used as an important biomarker for the diagnosis of breast cancer.

cancer biology↗

bioRxiv2023

DPHL v2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins.

A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v1, a previous pan-human library built from 1096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying 10,943 proteins. However, a major limitation of DPHL v1 is the lack of semi-tryptic peptides and protein isoforms, which are abundant in clinical specimens. Here, we generated DPHL v2 from 1608 DDA-MS data acquired using Orbitrap mass spectrometers. The data included 586 DDA-MS newly acquired from 17 tissue types, while 1022 files were derived from DPHL v1. DPHL v2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v2 to include semi-tryptic peptides and protein isoforms. DPHL v2 was then applied to a publicly available colorectal cancer dataset with 286 DIA-MS files. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v1. Our findings show that the increased human proteome coverage of DPHL v2 provides larger pools of potential protein biomarkers.

bioinformatics↗

bioRxiv2023

ATP-releasing SWELL1 channel in spinal microglia contributes to neuropathic pain

Following peripheral nerve injury, extracellular ATP-mediated purinergic signaling is crucial for spinal cord microglia activation and neuropathic pain. However, the mechanisms of ATP release remain poorly understood. Here, we show that volume-regulated anion channel (VRAC) is an ATP-releasing channel and is activated by inflammatory mediator sphingosine-1-phosphate (S1P) in microglia. Mice with microglia-specific deletion of Swell1 (also known as Lrrc8a), a VRAC essential subunit, had reduced peripheral nerve injury-induced increase in extracellular ATP in spinal cord. The mutant mice also exhibited decreased spinal microgliosis, dorsal horn neuronal hyperactivity, and both evoked and spontaneous neuropathic pain-like behaviors. We further performed high-throughput screens and identified an FDA-approved drug dicumarol as a novel and potent VRAC inhibitor. Intrathecal administration of dicumarol alleviated nerve injury-induced mechanical allodynia in mice. Our findings suggest that ATP-releasing VRAC in microglia is a key spinal cord determinant of neuropathic pain and a potential therapeutic target for this debilitating disease.

physiology↗

bioRxiv2023

Abnormal expression of Prolyl oligopeptidase (POP) and its catalytic products Ac-SDKP contributes to the ovarian fibrosis change in Polycystic ovary syndrome (PCOS) mice

Polycystic ovary syndrome (PCOS) is an endocrine disorder and metabolic syndrome. Ovarian fibrosis pathological change in PCOS gradually attracted peoples attention. In this study, we constructed PCOS mice model through dehydroepiandrosterone. Sirius red staining showed that the ovarian tissues in PCOS mice had obvious fibrosis. Prolyl oligopeptidase(POP) is a serine protease and N-acetyl-Seryl-aspartyl-Lysyl-proline (Ac-SDKP) is its catalytic products. Studies show that abnormal expression and activity of POP and Ac-SDKP are closely related to tissue fibrosis. We found that the expression of POP and Ac-SDKP was decreased in ovaries of PCOS mice. Further studies showed that POP and Ac-SDKP promoted the expression of Matrix metalloproteinases 2 (MMP-2) expression and decreased the expression of transforming growth factor beta 1 (TGF-{beta}1) in granulosa cells. Hyperandrogenemia is a typical symptom of PCOS. We found that testosterone induced the low expression of POP and MMP2, and high expression of TGF-{beta}1 in granulosa cells. POP overexpression and Ac-SDKP treatment inhibited the effect of testosterone on TGF-{beta}1 and MMP2 in vitro and ovarian fibrosis in PCOS mice model. In conclusion, PCOS ovarian tissue showed obvious fibrosis. Low expression of POP, Ac-SDKP and changes in fibrotic factors contribute to the ovarian pathological fibrosis induced by androgen.

cell biology↗

bioRxiv2023

Establishment of primary renal lymphoma model and the clinical relevance

Extranodal dissemination was an important feature of aggressive B-cell lymphoma. Due to the lack of available animal model, the causes of extranodal dissemination of lymphoma were largely unknown. Here, we identified a novel cell line, named MA-K, which originated from the E-Myc;Cdkn2a-/- cell line, named MA-LN in this study. Compared to MA-LN, MA-K tended to disseminate in the kidney rather than lymph nodes in lymphoma transplantation model, resembling human primary renal lymphoma. The transcriptome analysis revealed that MA-K had undergone the transcriptional evolution during the culture. Specialized transcriptional pattern analysis, we proposed in this study, identified that FOXO1-BTG1-MYD88 pattern was formed in MA-K. Further analysis found that translation pathway was the most enriched pathway in specially expressed genes (SEGs) in MA-K. Among the SEGs, 3 up-regulated genes, RPLP2, RPS16 and MRPS16, and 5 down-regulated genes, SSPN, CD52, ANKRD37, CCDC82 and VPREB3, in MA-K were identified as promising biomarkers to predict the clinical outcomes of human DLBCL. Moreover, the joint expression of the 5-gene signature could effectively predict clinical outcomes of human DLBCL in triple groups. These findings suggested that the MA-K cell line had strong clinical relevance with human aggressive B-cell lymphoma. Moreover, the MA-K primary renal lymphoma model, as a novel syngenetic mouse model, would be greatly useful for both the basic research on lymphoma dissemination and preclinical efficacy evaluation of chemotherapy and immunotherapy.

cancer biology↗

bioRxiv2023

EFNB1 level affects drug response in DLBCL cell lines

Targeted therapy was a promising therapy for aggressive B-cell lymphoma. However, drug resistance was still an unavoidable problem. Here, we explored the effect of EFNB1 on drug response. Analysis of IC50 data showed that high level of EFNB1 was associated with resistance to most targeted drugs targeting BCR in human DLBCL cell lines. Drug response assay showed that Efnb1 could enhance SRC phosphorylation and increased the sensitivity of cells to SRC inhibitors. Meanwhile, Efnb1 could sensitize cells to most cytotoxic drugs, especially DOX and VCR. Efnb1 could confer cells sensitivity to VCR by enhancing the phosphorylation of Stmn1 at serine 28. Survival analysis revealed that the expression level of genes phosphorylated in Efnb1 cells were associated with poor prognosis of human DLBC. Together, this study revealed that EFNB1 level, as a non-genetic mechanism, greatly affected drug response of targeted drugs and cytotoxic drugs through the phosphorylation network. Our findings would provide important insights into EFNB1-SRC activated B-cell lymphoma and efficacy evaluation.

pharmacology and toxicology↗

bioRxiv2022

Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction

RNAs are fundamental in living cells and perform critical functions determined by the tertiary architectures. However, accurate modeling of 3D RNA structure remains a challenging problem. Here we present a novel method, DRfold, to predict RNA tertiary structures by simultaneous learning of local frame rotations and geometric restraints from experimentally solved RNA structures, where the learned knowledge is converted into a hybrid energy potential to guide subsequent RNA structure constructions. The method significantly outperforms previous approaches by >75.6% in TM-score on a nonredundant dataset containing recently released structures. Detailed analyses showed that the major contribution to the improvements arise from the deep end-to-end learning supervised with the atom coordinates and the composite energy function integrating complementary information from geometry restraints and end-to-end learning models. The open-source DRfold program allows large-scale application of high-resolution RNA structure modeling and can be further improved with future release of RNA structure databases.

bioinformatics↗

bioRxiv2022

Understanding prefrontal cortex functions by decoding its molecular, cellular and circuit organization

The prefrontal cortex (PFC) is functionally one of the most complex regions of mammalian brain. Unlike other cortical areas that process single sensory modalities (like vision, touch, smell, etc.), the PFC integrates information across brain regions to regulate diverse functions ranging from cognition, emotion, executive action to even pain sensitivity. However, it is unclear how such diverse functions are organized at the cellular and circuit levels within the anatomical modules of the PFC. Here we employed spatially resolved single-cell transcriptome profiling to decode PFCs organizational heterogeneity. The results revealed that PFC has very distinct cell type composition relative to all neighboring cortical areas. Interestingly, PFC also adopts specialized transcriptional features, different from all neighbors, with differentially expressed genes regulating neuronal excitability. The projections to major subcortical targets of PFC emerge from combinations of neuron subclusters determined in a target-intrinsic fashion. These cellular and molecular features further segregated within subregions of PFC, alluding to the subregion-specific specialization of several PFC functions. Finally, using these unique cellular, molecular and projection properties, we identified distinct cell types and circuits in PFC that engage in pathogenesis of chronic pain. Collectively, we not only present a comprehensive organizational map of the PFC, critical for supporting its diverse functions, but also reveal the cluster and circuit identity of a pathway underlying chronic pain, a rapidly escalating healthcare challenge limited by molecular understanding of maladaptive PFC circuits. Major pointsO_LIPFC adopts unique cellular composition, distinct from other cortical areas C_LIO_LISelective transcriptomic features emerge in PFC to support its divergent functional portfolio C_LIO_LISubcortical projections of PFC assume target-intrinsic specification for innervating clusters C_LIO_LIA molecularly defined L5 projection neuron cluster (to PAG) potentially mediates chronic pain pathogenesis C_LI

neuroscience↗

bioRxiv2022

Metal-driven anaerobic oxidation of methane as an important methane sink in methanic cold seep sediments

Anaerobic oxidation of methane (AOM) coupled with reduction of metal oxides is supposed to be a globally important bioprocess in marine sediments. However, the responsible microorganisms and their contributions to methane budget are not clear in deep sea cold seep sediments. Here, we combined geochemistry, muti-omics and numerical modeling to study metal-dependent AOM in methanic cold seep sediments in the northern continental slope of the South China Sea. Geochemical data based on methane concentrations, carbon stable isotope, solid-phase sediment analysis and pore water measurements indicate the occurrence of anaerobic methane oxidation coupled to metal oxides reduction in the methanic zone. The 16S rRNA gene amplicons and transcripts, along with metagenomic and metatranscriptomic data suggest that diverse ANME groups actively mediated methane oxidation in the methanic zone either independently or in syntrophy with e.g. ETH-SRB1 as potential metal reducers. Modeling results suggest that the estimated rates of methane consumption via Fe-AOM and Mn-AOM were both 0.3 mol cm-2 yr-1, which account for [~]3% of total CH4 removal in sediments. Overall, our results highlight metal-driven anaerobic oxidation of methane as an important methane sink in methanic cold seep sediments.

microbiology↗

bioRxiv2022

Microbiome features differentiating unsupervised-stratification based clusters of patients with abnormal glycometabolism

The alteration of gut microbiota structure plays a pivotal role in the pathogenesis of abnormal glycometabolism. However, the microbiome features identified in patient groups stratified solely based on glucose levels remain controversial among different studies.. In this study, we stratified 258 participants (discovery cohort) into three clusters according to an unsupervised method based on 16 clinical parameters involving the levels of blood glucose, insulin, and lipid. We found 67 cluster-specific microbiome features (i.e., amplicon sequence variants, ASVs) based on 16S rRNA gene V3-V4 region sequencing. Specifically, ASVs belonging to Barnesville and Alistipes were enriched in Cluster 1, in which participants had the lowest blood glucose levels, high insulin sensitivity, and high-fecal short-chain fatty acid concentration. ASVs belonging to Prevotella copri and Ruminococcus gnavus were enriched in Cluster 2, which was characterized by a moderate level of blood glucose, serious insulin resistance, and high levels of cholesterol and triglyceride. Cluster 3 was characterized by a high level of blood glucose and insulin deficiency, enriched with ASVs in P. copri and Bacteroides vulgatus. In addition, machine learning classifiers using the 67 cluster-specific ASVs were used to distinguish individuals in one cluster from those in the other two clusters both in discovery and testing cohorts (N = 83). Therefore, microbiome features identified based on the unsupervised stratification of patients with more inclusive clinical parameters may better reflect microbiota alterations associated with the progression of abnormal glycometabolism. IMPORTANCEThe gut microbiota is altered in patients with type 2 diabetes (T2D) and prediabetes. The association of particular bacteria with T2D, however, varied among studies, which has made it challenging to develop precision medicine approaches for the prevention and alleviation of T2D. Blood glucose level is the only parameter in clustering patients when identifying the T2D-related bacteria in previous studies. This stratification ignores the fact that patients within the same blood glucose range differ in their insulin resistance and dyslipidemia, which also may be related to disordered gut microbiota. In addition to parameters of blood glucose levels, we also used additional parameters involving insulin and lipid levels to stratify participants into three clusters and further identified cluster-specific microbiome features. We further validated the association between these microbiome features and glycometabolism with an independent cohort. This work highlights the importance of stratification of patients with blood glucose, insulin, and lipid levels when identifying the microbiome features associated with the progression of abnormal glycometabolism.

microbiology↗

bioRxiv2022

Acidovorax temperans polarizes T17 cells and skews neutrophil maturation to promote lung adenocarcinoma development

Dysbiosis, or changes within the microbiome, is a common feature of solid tumors, however whether this dysbiosis directly contributes to tumor development is largely unknown. We previously characterized the lung cancer microbiome and identified Acidovorax temperans as enriched in tumors. In this study, we instilled A. temperans in an animal model driven by mutant Kras and Tp53 alleles. This revealed A. temperans accelerates tumor development and burden through infiltration of proinflammatory cells. Neutrophils exposed to A. temperans displayed a mature, pro-tumorigenic genotype with increased cytokine signaling, with a global shift away from IL-1{beta} signaling. Neutrophil to monocyte and macrophage signaling upregulated MHC II to activate CD4+ T cells which polarized to an IL-17A+ phenotype detectable in CD4+ and {gamma}{delta} populations. T17 cells shared a common gene expression program predictive of poor survival in human LUAD. These data indicate dysbiosis promotes tumor growth by modulating inflammation.

cancer biology↗

bioRxiv2022

A histone methyltransferase point mutation demonstrates a mechanism for translocation-driven acute leukemias

Our understanding of acute leukemia pathology is heavily dependent on 11q23 chromosomal translocations involving the mixed lineage leukemia-1 (MLL1) gene, a key player in histone H3 lysine 4 (H3K4) methylation. These translocations result in distinct MLL1-fusion (MLL1F) proteins that are thought to drive leukemogenesis. However, the mechanism behind increased H3K4 trimethylation in MLL1F-leukemic stem cells (MLL1F-LSCs), following loss of catalytic SET domain of MLL1 (known for H3K4 mono- and dimethylation), remains unclear. In our investigation, we introduced a homozygous loss-of-function point mutation in MLL1 within human induced pluripotent stem cells. Remarkably, this mutation mimics the histone methylation, gene expression, and EMT phenotypes of MLL1F-LSCs- without the need for a translocation or functional wild-type MLL1. This observation underscores the essential role of MLL1s enzymatic activity in restraining the cascade of epigenetic changes associated with the gene activating H3K4 trimethylation mark, which we show is catalyzed by mislocalized SETd1a H3K4 trimethyltransferase in the absence of MLL1s enzymatic activity. Challenging existing models, our findings imply that MLL1F-induced leukemias arise from a dominant-negative impact on MLL1s histone methyltransferase activity. We advocate for a therapeutic paradigm shift, targeting SETd1a for precision medicine. This work opens new avenues for addressing the complexities of MLL1-associated leukemias and improving targeted therapies. SummaryEpigenomic and gene expression changes in iPS cells with a mutated MLL1 histone methyltransferase suggest an oncogenic mechanism for MLL1-fusion leukemias.

cancer biology↗

bioRxiv2022

Patterns of gene expression and allele-specific expression vary among macular tissues and clinical stages of Age-related Macular Degeneration

Age-related macular degeneration (AMD) is a complex neurodegenerative disease and is the leading cause of blindness in the aging population. Early AMD is characterized by drusen in the macula and causes minimal changes in visual function. The later stages are responsible for the majority of visual impairment and blindness and can be either manifest as geographic atrophy (dry) or neovascular disease (wet). Available medicines are directed against the wet form and do not cure vision loss. Therefore, it is imperative to identify preventive and therapeutic targets. As the mechanism for AMD is unclear, we aim to interrogate the disease-affected tissue - the macular neural retina and macular retina pigment epithelium (RPE)/choroid. We investigated differentially expressed genes expression (DEG) across the clinical stages of AMD in meticulously dissected and phenotyped eyes using a standardized published protocol (Owen et al., 2019). Donor eyes (n=27) were obtained from Caucasian individuals with an age range of 60-94 and 63% were male, and tissue from the macula RPE/choroid and macula neural retina were taken from the same eye. Donor eyes were recovered within 6 hours post mortem interval time to ensure maximal preservation of RNA quality and accuracy of diagnosis. Eyes were then phenotyped by retina experts using multi modal imaging (fundus photos and SD-OCT). Utilizing DESeq2, followed PCA, Benjamini Hochberg adjustment to control for the false discovery rate, and Bonferonni correction for the number of paired comparisons: a total of 26,650 genes were expressed in the macula RPE/choroid and/or macula retina among which significant differential expression was found for 1,204 genes between neovascular AMD and normal eyes, 40 genes between intermediate AMD and normal eyes, and 1,194 genes between intermediate AMD and neovascular AMD. A comparison of intermediate AMD versus normal eyes included TCN2, PON1, IFI6, GPR123, and TIMD4 as being some of the most significant DEGs in the macula RPE/choroid. A comparison of neovascular AMD versus normal eyes included SLC1A2, SLC24A1, SCAMP5, PTPRN, and SEMA7A as being some of the most significant DEGs in the macula RPE/choroid. Top pathways of DEGs in the macular RPE/choroid identified through Ingenuity Pathway Analysis (IPA) for the comparison of intermediate AMD with normal eyes were interferon signaling and Th1 and Th2 activation, while those for the comparison of neovascular AMD with normal eyes were the phototransduction and SNARE signaling pathways. Allele-specific expression (ASE) in coding regions of previously reported AMD risk loci identified by GWAS (Fritsche et al, 2016) revealed significant ASEs for C3 rs2230199 and CFH rs1061170 in the macula RPE/choroid for normal eyes and intermediate AMD, and for CFH rs1061147 in the macula RPE/choroid for normal eyes and intermediate and neovascular AMD. An investigation of the 34 established AMD risk loci revealed that 75% of them were significantly differentially expressed between normal macular RPE/choroid and macular neural retina, with 75% of these loci showing higher expression in the RPE. Similarly, disease state differences for the GWAS loci were only found to be statistically differentially expressed in the macular RPE/choroid. Moreover, the known coding variants in the previously identified GWAS loci including, CFH, C3, CFB, demonstrated ASE across AMD clinical stages in the macular RPE/choroid and not in the neural retina. These data at the bulk level underscore the importance of the RPE/choroid to AMD pathophysiology. While many bulk RNASeq data sets are publicly available, to the best of our knowledge this is one of the first publicly available datasets with both maculae RPE/choroid and macula neural retina from the same well phenotyped donor eye(s) where the macula is separated from the periphery. Our findings also underscore the importance of studying both macular tissue types to gain a full understanding of mechanisms leading to AMD. Our results provide insights into underlying biological mechanisms that may differentiate the disease subtypes and into the tissues affected by the disease.

genomics↗

bioRxiv2022

Identification of a key genetic factor governing arabinan utilization in the gut microbiome suggests a novel therapeutic target for constipation

Probiotics have been widely used to improve impaired gastro-intestinal motility, yet their efficacy varied substantially across strains. Here, by a large-scale genetic screen plus in vivo measurements, we identified a key genetic factor (abfA cluster governing arabinan utilization) in probiotic Bifidobacterium longum harnessing the treatment efficacy against functional constipation (FC). Intriguingly, it also presents in a range of gut resident microbiota and played a protective role against FC. Next, our longitudinal multi-omics study in humans revealed that the exogenous abfA-cluster- carrying B. longum can well establish itself in the gut, and enrich arabinan-utilization residents and beneficial metabolites (e.g., acetate, butyrate, chenodeoxycholic acid and uracil). Finally, transplantation of abfA-cluster-enriched human microbiota to FC- induced germ-free mice recapitulated the marked gut-motility improvement and elevated production of beneficial metabolites. Collectively, our proof-of-concept study actively demonstrated a critical yet underexplored role of microbial abfA cluster in ameliorating FC, establishing generalizable principles for developing functional-genomics-directed probiotic therapies.

microbiology↗

bioRxiv2022

Trans-cellular control of synapse properties by a cell type-specific splicing regulator

The recognition of synaptic partners and specification of synaptic properties are fundamental for the function of neuronal circuits. Terminal selector transcription factors coordinate the expression of terminal gene batteries that specify cell type-specific properties. Moreover, pan-neuronal alternative splicing regulators have been implicated in directing neuronal differentiation. However, the cellular logic of how splicing regulators instruct specific synaptic properties remains poorly understood. Here, we combine genome-wide mapping of mRNA targets and cell type-specific loss-of-function studies to uncover the contribution of the nuclear RNA binding protein SLM2 to hippocampal synapse specification. Focusing on hippocampal pyramidal cells and SST-positive GABAergic interneurons, we find that SLM2 preferentially binds and regulates alternative splicing of transcripts encoding synaptic proteins, thereby generating cell type-specific isoforms. In the absence of SLM2, cell type-specification, differentiation, and viability are unaltered and neuronal populations exhibit normal intrinsic properties. By contrast, cell type-specific loss of SLM2 results in highly selective, non-cell autonomous synaptic phenotypes, altered synaptic transmission, and associated defects in a hippocampus-dependent memory task. Thus, alternative splicing provides a critical layer of gene regulation that instructs specification of neuronal connectivity in a trans-synaptic manner.

neuroscience↗