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Sheng, J.

Publications and source records attributed to Sheng, J..

At least 19 recordsLinked to original sources

Evolution-Guided Engineering of Non-conserved N-Glycosylation Sites Improves Heterologous Production of Sulfotransferases

Escherichia coli features low cost, mature fermentation technology and high recombinant protein output, but the expression of glycosylation-dependent eukaryotic proteins therein is severely limited. Many glycosylated proteins are key tool enzymes for the biosynthesis of various pharmaceutical molecules, such as glycosaminoglycan-related synthases, but there is a lack of universal protein engineering methods to enable the adaptive evolution of these enzymes in E. coli. We established an evolution-guided optimization strategy that targets non-conserved N-glycosylation sites (EGO-NGly). The core of this strategy lies in the phylogeny-guided selective reversion of evolutionarily acquired N-glycosylation sequons to naturally occurring non-glycosylated residues from early-divergent orthologs, thereby improving heterologous production and residual activity stability for selected sulfotransferases in E. coli. Using heparin 3-O-sulfotransferase 1 (3OST-1) as a model enzyme apparatus in eukaryotic organisms, EGO-NGly extended the residual activity half-life by 4.5-fold. Structural analysis and molecular dynamics simulations indicate that greater surface rigidity and remodeling of intramolecular interaction networks contribute to the improved conformational stability of M7 in an aglycosylated host. EGO-NGly was further applied to a panel of 3OST and 6OST homologs, demonstrating its applicability to a subset of the tested enzymes. Furthermore, EGO-NGly can be orthogonally integrated with other complementary protein engineering strategies, as exemplified by its combination with the machine learning-aided Protein Repair One-Stop Service, generating variants with 8-fold and 17-fold extensions in residual activity half-life. Collectively, these results establish EGO-NGly as a practical and potentially cost-effective engineering strategy for improving the prokaryotic expression and functional performance of selected glycosylation-dependent eukaryotic sulfotransferases.

biochemistry↗

The Wobble Uridine tRNA Writer MnmA Shapes Codon-Dependent Stress Response Systems

Escherichia coli uses wobble uridine (U34) modifications to tune codon decoding, but how individual tRNA writer enzymes shape gene expression remains unclear. Here, we identify MnmA, the U34 thiolation enzyme for tRNALys, tRNAGln, and tRNAGlu, as a central regulator linking codon-directed translation to regulon control and stress response. Loss of MnmA depleted s2U-dependent wobble modifications, preventing geranyl-(ges2U) and seleno-(se2U)-based modifications, causing growth defects, reduced catalase activity, and multi-level gene expression dysregulation. The {Delta}mnmA cells showed broad adaptive transcriptional reprogramming associated with RpoS- and OxyR-regulated pathways, which was accompanied by compromised protein output. Endogenous and tagged-protein analyses revealed specific impairment of transcriptional regulators, adaptive and detoxification proteins, including RpoS, OxyR, FliA, KatE, and KatG. Polysome profiling and polysome-associated RNA sequencing showed that MnmA deficiency globally reduces translational capacity and uncouples mRNA abundance from translational efficiency, which is exacerbated during oxidative stress. We developed genome-wide codon-usage mapping analytics to identify five codon-defined gene clusters, with specific clusters enriched for Lys, Gln, and Glu codons disproportionately affected by MnmA loss. Together, these findings support that wobble uridine thiolation and downstream modifications pair with corresponding codon architecture to coordinate the translation of regulon controllers and stress-response networks linked to bacterial fitness. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=159 HEIGHT=200 SRC="FIGDIR/small/745044v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1a4058borg.highwire.dtl.DTLVardef@167f4cdorg.highwire.dtl.DTLVardef@1f8c7a8org.highwire.dtl.DTLVardef@1fc0767_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

Dissociable structural and molecular pathways of age-related change in sustained attention

Sustained attention, the capacity to maintain goal-directed attention over extended periods, declines with age but with substantial individual variability across cognitively unimpaired (CU) older adults. We sought to determine the contributions of microstructural deterioration of the superior longitudinal fasciculus (SLF), the principal white-matter tract coupling prefrontal and parietal nodes of the dorsal attention network, as well as markers of preclinical Alzheimers disease (AD) to individual differences in sustained attention in ageing. In 162 CU older adults (mean (SD) age = 73.0 (4.9), %F = 64.8) drawn from two Stanford ageing cohorts, we measured sustained attention using the gradual-onset Continuous Performance Task (gradCPT). Performance was indexed by a composite score (Att-Z) derived from discriminability (d') and response-time variability (RTV). We used diffusion MRI tractography to quantify SLF fractional anisotropy (FA) and mean diffusivity (MD) alongside two control tracts, the corticospinal tract (CST) and cingulum (CGC). NULISA multiplex plasma immunoassays were used to measured AD-related pathology (pTau-181, pTau-217), neuroaxonal injury (NfL), and astrocytic reactivity (GFAP; plasma subsample N = 146). Parallel mediation and commonality analyses tested whether structural and plasma biomarker pathways contribute independently to individual differences in sustained attention function. Older age was associated with lower Att-Z ({beta} = -0.315, p < 0.001). In simultaneous three-tract regression models, only SLF microstructure uniquely predicted Att-Z (FA: {beta} = +0.275, p < 0.001; MD: {beta} = -0.320, p < 0.001). SLF microstructure mediated the age-attention relationship (FA indirect {beta}unstandardised = -0.01, pboot <0.01, MD indirect {beta}unstandardised = -0.009 to -0.01, pboot <0.05). Plasma pTau-181 ({beta} = -0.212, pFDR < 0.03), pTau-217 ({beta} = -0.163, pFDR < 0.05), and NfL ({beta} = -0.156, pFDR < 0.05) were negatively associated with Att-Z and each mediated effects of age on performance (pTau-181 indirect {beta}unstandardised = -0.008, pboot < 0.01; pTau-217 indirect {beta}unstandardised= -0.006, pboot< 0.05; NfL indirect {beta}unstandardised = -0.011, pboot< 0.05), whereas GFAP showed no association with sustained attention in any model. SLF microstructure was negatively associated with age (FA {beta} = -0.207, p < 0.01; MD {beta} = +0.270, p < 0.001) but was not significantly associated with plasma biomarkers (all p > 0.10). In parallel mediation models, SLF microstructure and plasma pTau exhibited significant independent indirect effects on Att-Z (SLF FA indirect {beta}unstandardised= -0.010, pboot< 0.01; SLF MD indirect {beta}unstandardised = -0.009 to -0.010, pboot< 0.05; pTau-181 indirect {beta}unstandardised = -0.008 to -0.009, pboot< 0.01; pTau-217 indirect {beta}unstandardised= -0.006 to -0.007, pboot< 0.05). Effects of NfL were attenuated when combined in a model with pTau (indirect {beta}unstandardised = -0.005 to -0.008, pboot> 0.15), suggesting shared variance among these markers. These findings reveal multiple pathways that contribute to individual differences in sustained attention in ageing that are detectable before clinical impairment, including SLF white matter integrity -- which is linked to the structural disconnection of the dorsal attention network -- and preclinical AD pathology. The independence of these pathways identifies two separable biological targets for preserving attentional capacity in CU older adults.

neuroscience↗

Decoding Spatial Programs in Human Glioblastoma Through Surprisal Information-Theoretical Analysis

Glioblastoma (GBM) is a highly heterogeneous and invasive brain tumor in which complex interactions among tumor cells, immune cells, and neurons shape disease progression and therapeutic resistance. Resolving spatial patterns programs in glioblastoma (GBM) requires analytical approaches that go beyond variance-driven embeddings. Here, we applied thermodynamic surprisal analysis, an information-theoretic decomposition framework, to spatial transcriptomic sequencing from human GBM specimens to identify orthogonal constraint modes that capture dominant and previously hidden spatial programs. Surprisal analysis revealed structured patterns in the data that are not highlighted by standard approaches such as PCA or cell type deconvolution, including immune-activation-associated signatures as well as spatial programs consistent with synapse remodeling. Coupling surprisal decomposition with spatial ligand-receptor interaction analysis, NICHES, along with multiplexed protein imaging connected these spatial hidden modes to reveal potential communication networks. Together, these results position surprisal analysis as a powerful, complementary strategy for interrogating spatial tumor architecture, enabling discovery of non-obvious spatial programs and interactions that are obscured by variance-based methods.

systems biology↗

CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space

Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feature extraction, and spatial organization analysis. However, these tools often require manual intervention and are not well integrated with code-driven automation, limiting efficiency and scalability for complex spatial tissue studies. In addition, they offer limited flexibility for custom analyses, as they typically support only a fixed set of pre-implemented spatial cellular features. To address these limitations, we propose CodeCytos, a coding-based reasoning agent framework that enables dynamic, programmable interaction with spatial molecular imaging data, to improve automation and customization. CodeCytos is designed to streamline the exploration of custom spatial cellular features and adapt to diverse research needs. We demonstrate its utility through case studies on four expert-curated datasets from distinct tissue types: frontal cortex, non-small-cell lung cancer, pancreas, and tonsil. We evaluate CodeCytos under a realistic minimal prompt setting, where bioscientists pose simple questions without task-specific instructions or contextual information about spatial cellular analysis, and benchmark multiple LLM backbones with strong coding capabilities. We further show that incorporating tailored, domain-agnostic few-shot in-context coding-reasoning examples (randomly sampled demonstrations outside the spatial analysis domain) can substantially improve performance without requiring costly, expert-crafted in-domain demonstrations. Overall, CodeCytos outperforms baseline approaches, highlighting the potential of code-action agents to assist with custom feature exploration in spatial molecular imaging and to accelerate biomarker discovery.

bioinformatics↗

Temperature and intrinsic Ca2+ reshape TRPM4 pharmacology

Proteins operate in dynamic environments where ions, lipids, and temperature collectively define their properties, yet most studies rely on simplified conditions that overlook these intrinsic variables. Here, we show two such factors--temperature and Ca2+-- remodel the function and pharmacology of TRPM4, an ion channel implicated in cardiac conduction, immune regulation, cancer, and intestinal fluid homeostasis. At physiological temperature and Ca2+, TPPO--previously considered a selective TRPM5 inhibitor inactive toward TRPM4--potently activates TRPM4, revealing strong synergy among temperature, Ca2+, and ligand binding. In contrast, Necrocide-1, a necroptotic activator targeting the same binding pocket, defies this logic: it opens TRPM4 without Ca2+ but is antagonized by Ca2+. Meanwhile, the inhibitors NBA and CBA engage a nearby pocket, locking the channel in a non-conductive pre-open state. Our findings highlight that even rigid binding pockets can exhibit temperature-dependent ligand recognition, revealing hidden pharmacology and informing selective, environment-aware therapeutic strategies.

biophysics↗

Inferring virtual cell environments using multi-agent reinforcement learning

1Single cells interact continuously to form a cell environment that drives key biological processes. Cells and cell environments are highly dynamic across time and space, fundamentally governed by molecular mechanisms, such as gene expression. Recent sequencing techniques measure single-cell-level gene expression under specific conditions, either temporally or spatially. Using these datasets, emerging works, such as virtual cells, can learn biologically useful representations of individual cells. However, these representations are typically static and overlook the underlying cell environment and its dynamics. To address this, we developed CellTRIP, a multi-agent reinforcement learning method that infers a virtual cell environment to simulate the cell dynamics and interactions underlying given single-cell data. Specifically, cells are modeled as individual agents with dynamic interactions, which can be learned through self-attention mechanisms via reinforcement learning. CellTRIP also applies novel truncated reward boot-strapping and adaptive input rescaling to stabilize training. We can in-silico manipulate any combination of cells and genes in our learned virtual cell environment, predict spatial and/or temporal cell changes, and prioritize corresponding genes at the single-cell level. We applied and benchmarked CellTRIP on various simulated and real gene expression datasets, including recapitulating cellular dynamic processes simulated by gene regulatory networks and stochastic models, imputing spatial organization of mouse cortical cells, predicting developmental gene expression changes after drug treatment in cancer cells, and spatiotemporal reconstruction of Drosophila embryonic development, demonstrating its outperformance and broad applicability. Interactive manipulation of those virtual cell environments, including in-silico perturbation, can prioritize spatial and developmental genes for single-cell-level changes, enabling the generation of new insights into cell dynamics over time and space. CellTRIP is open source as a general tool and available at github.com/daifengwanglab/CellTRIP.

bioinformatics↗

Abnormally increased intrinsic neural timescales in sensory and default mode networks in cocaine use disorder

Cocaine use disorder (CUD) is associated with abnormal structural and functional brain changes. However, the neurodynamics and molecular underpinnings remain unclear. In this study, we mapped whole-brain intrinsic neural timescales (INTs), reflecting temporal neural processing, using resting-state functional magnetic resonance imaging data from 44 CUD patients and 44 healthy controls (HC). CUD showed increased INTs in visual, somatomotor, and default mode networks compared with HC. Mediation analysis linked local INTs abnormalities to altered dorsal attention network neurodynamics, associated with inhibitory control deficits. Notably, these changes were primarily correlated with alterations in gamma-aminobutyric acid type A receptors and the noradrenaline transporter. Machine learning classifiers based on INTs achieved a maximum accuracy of 75.5% in distinguishing CUD from HC, with a generalization accuracy of 65.0% on an independent dataset. This study elucidates aberrant neural mechanisms underlying CUD and highlights INTs as promising diagnostic biomarkers for clinical detection and intervention. TeaserSpatiotemporal neuroscience reveals intrinsic neural timescale disruptions underlying cocaine use disorder, offering novel diagnostic biomarkers.

neuroscience↗

Dynamic landscapes of gene regulatory networks in early mammalian neurogenesis: Insights into brain evolution and disorder risk

Neurogenesis--the process of generating neurons--is governed by dynamic transcriptional programs that vary across time, brain regions, and cell types, forming regionally specialized neuronal circuits. To understand these dynamics, we constructed a comprehensive gene regulatory network (GRN) resource encompassing 22 neurogenic lineages from human, macaque, and mouse, enabling cross-species and cross-regional comparisons. Leveraging state-of-the-art trajectory analysis and GRN inference, we characterized temporal regulatory dynamics and introduced a "dynamic score" to identify key subnetworks with lineage-specific dynamics, including hundreds of regulons and co-regulatory modules. Our analysis uncovered both known and novel candidate regulators driving neuronal differentiation and regional identity, spanning the entire human brain, as well as evolutionary divergence in neurogenic GRNs distinguishing human brains. Mapping risk genes to the resource helped understand associated early gene regulatory dynamics with 35 neurodevelopmental disorders and traits including autism, schizophrenia, severe intellectual disability, and microcephaly. This resource is publicly available as an interactive online platform.

developmental biology↗

Molecular and cellular processes disrupted in the early postnatal Down syndrome prefrontal cortex

Down syndrome is the most common genetic cause of intellectual disability and is characterized by early-onset delays in motor, cognitive, and language development. The molecular mechanisms underlying these neurodevelopmental impairments remain poorly understood. Here, we utilized single-nucleus multiomic sequencing to simultaneously profile gene expression and chromatin accessibility in the Down syndrome prefrontal cortex during early postnatal development, a critical period for synaptogenesis, neural maturation, and developmental neuroimmune interactions. Our findings reveal widespread dysregulation of chromatin accessibility and gene expression, with deficits spanning metabolic and synaptic pathways, oligodendrocyte lineage progression, and a pronounced neuroinflammatory signature. We present a molecular atlas of Down syndrome neuropathology at a critical stage of brain development, highlighting convergent neurodevelopmental and neurodegenerative pathways and informing potential targeted therapies for Down syndrome-associated neuroinflammation.

neuroscience↗

Synergistic effects of APOE ϵ4 and Alzheimer's pathology on the neural correlates of episodic remembering in cognitively unimpaired older adults

Amyloid-{beta} (A{beta}) and tau pathology begin accumulating decades before clinical symptoms and are influenced by APOE {varepsilon}4, a key genetic risk factor for Alzheimers disease (AD). Although the presence of A{beta}, tau, and APOE {varepsilon}4 are thought to impact brain function, their effects on the neural correlates of episodic memory retrieval in preclinical AD remains unknown. We investigated this question in 159 cognitively unimpaired older adults (mean age, 68.9{+/-}5.8 years; 57% female) in the Stanford Aging and Memory Study. Participants completed an associative memory task concurrent with functional MRI. A{beta} was measured using CSF A{beta}42/A{beta}40 or Florbetaben-PET imaging and tau was measured using CSF pTau181. Hippocampal univariate activity and cortical reinstatement - that is, reinstatement of patterns of neocortical activity that were present during memory encoding - were measured during successful memory retrieval. Analyses revealed that APOE {varepsilon}4 was independently associated with greater A{beta} and tau burden, and that associations of AD biomarkers with brain function and memory were moderated by APOE {varepsilon}4. Among APOE {varepsilon}4 non-carriers, A{beta} burden was linked to a pattern of hippocampal hyperactivity. Among APOE {varepsilon}4 carriers, CSF pTau181 was linked to weaker cortical reinstatement during memory retrieval and lower memory performance. Thus, abnormal AD biomarkers and genetic risk synergistically impact neural and behavioral expressions of memory in preclinical AD. These findings highlight the critical role of APOE {varepsilon}4 in moderating effects of AD pathology on brain function and identify candidate mechanisms that may contribute to increased risk of memory impairment in preclinical AD. Significance StatementHippocampus-dependent cortical reinstatement is a critical mechanism supporting episodic remembering that contributes to individual differences in memory performance in older adults. However, the contribution of early Alzheimers disease (AD) pathology to variability in this mechanism is unknown. We demonstrate that associations of AD biomarkers with hippocampal activity and cortical reinstatement are moderated by APOE {varepsilon}4 in cognitively unimpaired older adults. Amyloid-{beta}-related hyperactivity was observed in the hippocampus among APOE {varepsilon}4 non-carriers, while CSF pTau181 was linked to weaker cortical reinstatement during memory retrieval and lower memory performance among APOE {varepsilon}4 carriers. Our findings highlight synergistic effects of APOE and AD pathology on brain function and identify candidate mechanisms that may underlie increased risk of memory impairment in preclinical AD.

neuroscience↗

Tracing the stemness and malignant transition in a heritable colorectal cancer Lynch Syndrome by single-cell RNA-seq analysis

BackgroundLynch Syndrome (LS) is an autosomal dominant disease characterized by germline heterozygous mutations in DNA mismatch repair (MMR) genes. High-risk LS patients may proceed to colorectal cancer (CRC). However, the drivers or biomarkers of LS benign colon tissue approaching malignant CRC are not completely understood. The similarity and difference between LS-related and nonLS-related CRC are also not well interrogated (LS-CRC vs. nonLS-CRC). This study aimed to understand the cellular changes during malignant transition in LS. MethodsSingle-cell RNA sequencing (scRNA-seq) was used to analyze paired biopsy samples from 3 patients with LS (cancer tissues vs. adjacent normal tissues, n=3). Single-nuclear RNA sequencing (snRNA-seq) was used to analyze a frozen biopsy sample from a patient with LS (n=1). scRNA-seq or snRNA-seq datasets from CRC were downloaded from the open source. Integrative computational analysis was performed to conclude the distinct pattern in the single-cell atlas. Immuno-histo-fluorescence staining (IHF) were also performed for three key markers. ResultsIn the single-cell atlas, we observed an increase in primitive cancer stem-cell-like cells with high expression of a general cancer biomarker CarcinoEmbryonic Antigen-related Cell Adhesion Molecule 5 (CEACAM5) in the epithelium of the LS. Infiltration of immune cells and DNA repair biological activity are dramatically increased in LS carcinoma. The burden in LS is fundamentally elevated compared to that in CRC or healthy donors when the mutations are in the coding-sequence-wide range. Furthermore, T cell and macrophage-related tumor immunity is readily mobilized in carcinomas compared to paraCArcinomas. ConclusionsThis study provides single-cell transcriptomic resource using affected tissues from patients with Lynch Syndrome and describes an integrative profile covering the alterations (cancer stem cell markers, mutation burden, and tumor immunity) during the malignant transition from healthy to Lynch Syndrome and to colorectal cancer at the single-cell level. Highlights and Figure/Table Index (Take-Home Messages)O_LIColon tissues from HD (n=4), patients with LS (n=6) and with CRC (n=3) were collected for snRNA-seq or scRNA-seq analysis; Diagnosis of the 6 LS patients are clearly supported by our pedigree documentations (Fig. 1 and Supp. Fig. 1) and briefed in Table 1; C_LIO_LIAmong the 6 patients with LS, 1 for snRNA-seq analysis (a carcinoma tissue only), 3 for scRNA-seq analysis (3 paired para-carcinoma and carcinoma tissues) and 3 for experimental validations; (Fig. 1) C_LIO_LIFollowing studies are focused on the comparisons between HD, LS and CRC; In addition, comparisons between paired carcinoma and para-carcinoma tissues from patients with LS were also performed; (Fig. 2-7) C_LIO_LIWhen HD and LS are compared, a cancer stem cell marker CEACAM5 is readily detected by snRNA-seq analysis; (Fig. 5) C_LIO_LIWhen carcinoma and para-carcinoma from LS patients are compared, increased immune cell infiltration of and enhanced DNA repair activity in the malignant tissues is readily detected by scRNA-seq analysis; in addition, three upregulated markers in LS carcinoma (BACE2, GRPC5A and OLFM4) were identified and validated by immunohistoinfloresnce; (Fig. 3 and Fig. 4) C_LIO_LISComatic algorithm-based mutation calling analysis suggests a comparable mutation burden between carcinoma and para-carcinoma from LS patients, but such mutation burdens are grossly greater than that from HD or that from patients with CRC; (Fig. 6) C_LI O_FIG O_LINKSMALLFIG WIDTH=170 HEIGHT=200 SRC="FIGDIR/small/647495v1_fig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@174af7dorg.highwire.dtl.DTLVardef@1ad3e71org.highwire.dtl.DTLVardef@dea1e4org.highwire.dtl.DTLVardef@568f91_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1C_FLOATNO Enrollment of LS patients and overall design of the study. (A) Three family pedigrees of the LS patients (LS-CRC) who donated the samples for single-cell transcriptomic analysis. Cropped pedigree information is provided in the Main text. See the Supp. Fig. 1 for the complete pedigree information. (B) Two different platforms were used in the study: snRNA-seq and scRNA-seq. (C) Various types of comparison were performed to characterize the malignant transition of LS. C_FIG O_TBL View this table: org.highwire.dtl.DTLVardef@eb8e4eorg.highwire.dtl.DTLVardef@cbafaaorg.highwire.dtl.DTLVardef@79ca83org.highwire.dtl.DTLVardef@1de7544org.highwire.dtl.DTLVardef@1e4fcbc_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONClinical information of enrolled patients with LS. An Excel version of the table is provided in the Supp. Material C_TABLECAPTION C_TBL O_FIG O_LINKSMALLFIG WIDTH=160 HEIGHT=200 SRC="FIGDIR/small/647495v1_fig2.gif" ALT="Figure 2"> View larger version (56K): org.highwire.dtl.DTLVardef@8cd71corg.highwire.dtl.DTLVardef@7e75b3org.highwire.dtl.DTLVardef@61757eorg.highwire.dtl.DTLVardef@68ca5f_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 2C_FLOATNO snRNA-seq analysis of a frozen colon biopsy sample from a LS patient reveals a cluster of cancer stem cells (A) Frozen colon biopsy samples were subjected for snRNA analysis (Healthy donors, N=4; Lynch Syndrome, N=1) and epithelial cells were filtered out for further study. Data were integrated by the Seurat and Harmony standard procedure. Clusters 0-9 were identified in a total of 11,353 cells (the Healthy Controls have 7,373 cells; the LS patient has 3,980 cells). The malignancy of the epithelial cells was inferred by the inferCNV and SCEVAN algorithm (two major compartments: tumor and no-tumor). The portion of tumor or non-tumor cells in each cluster was also illustrated (right panel). Note that the major contributor in Cluster 4, 6, and 7 is the tumor-like cells from the LS patient. (B) Each cluster of the epithelial cells was further annotated according to the combination of Seurat cluster identity and SCEVAN malignant identity. Mix_1 to 5 contain both tumor-like cells and non-tumor-like cells; Other clusters are marked as BEST4+-Enterocytes, Enterocytes and Goblet cells where much fewer tumor-like cells were assigned. Note that the epithelial cells from the LS patient are mainly classified into Mix_2, 4, and 5 tumor-like cells. (C) Three clones were inferred by SCEVAN algorithm. In the phylogenetic tree, Clone_1 and Clone_2 are closer and probably originated from Clone_3. (D) A Sankey plot showing overall belonging relationships in the epithelial snRNA-seq dataset. Note that the Mix_2 pool is dominated by cells from Lynch_01 and that in the Mix_2 pool Clone_3 is the most dominant clone. (E) The Mix_2 cells specifically express numerous colon epithelial stem cells signature markers such as SMOC2, RGBM, OLFM4, AXIN2 and LGR5. Of note, all these intestine stem cell signature genes were reported as marker genes for cancer stem cells, especially LGR5. (F) Pseudotime trajectory analysis of the Lynch Syndrome epithelium cells indicates the Mix_2 cells are the most primitive in development. (G) Top 36 differentially expressed genes (DEGs, both upregulated and downregulated) were highlighted when the non-tumor-like cells were compared with tumor-like cells in the Mix2. (H) The Mix_2, 4, 5 epithelial cells all have enriched signaling pathways involved in DNA repair response and MYC targets (fonts in red) while Mix_4 and 5 manifest Interferon alpha or gamma response (fonts in blue). C_FIG O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/647495v1_fig7.gif" ALT="Figure 7"> View larger version (54K): org.highwire.dtl.DTLVardef@1be2c6aorg.highwire.dtl.DTLVardef@55f267org.highwire.dtl.DTLVardef@9d60fborg.highwire.dtl.DTLVardef@4a2d37_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 7C_FLOATNO Distinct tumor immunity microenvironment profiles in LS carcinoma (A) T cells from LS-CA and LS-paraCA patients were filtered for further annotation. The LS-paraCA group had 1410 T cells, whereas the Lynch CA group had 2125 T cells. Six major T cell subtypes were identified: Naive CD4-T, NKT, Treg, IL7R+CD8_T, GZMA+CD8_T, and GZMK+CD8_T. Note that GZMA+CD8_T cells appear to be more abundant in Lynch CA (arrows). (B) The pseudotime trajectory indicating the T cells developed towards two branches: the Naive CD4-T and Treg branches, and GZMA+CD8_T and GZMK+CD8_T branches. GZMA+CD8_T cells appear to be more mature in LS-CA than in LS-paraCA (arrows). (C-F) Biological function-instructed scoring of the paired single-cell datasets of T cells from the three LS patients, including T cell cytotoxicity (B), T cell exhaustion (C), T cell immune escape (D), and T cell surveillance (E). (G) Circle plots showing interaction profiles across indicated cells in the paired LS samples. The direction of the lines indicates the direction of the cell-cell communication, the width of the lines indicates the interaction strength, and the color of the lines indicates the cell types of the senders. (H) Summary of the Study. In this study, we profiled Lynch Syndrome biopsy samples using single-cell or single-nucleus RNA-seq analysis. Paired carcinoma and adjacent para-carcinoma samples were included to facilitate the analysis, including tracing tumor clones, calculating mutation burden, identifying biomarkers for cancer stem cells, and tumor immune microenvironment changes during the transition from pre-carcinoma to carcinoma in the inheritable cancer Lynch Syndrome. See the text in the Discussion section for further detail. C_FIG O_FIG O_LINKSMALLFIG WIDTH=148 HEIGHT=200 SRC="FIGDIR/small/647495v1_fig5.gif" ALT="Figure 5"> View larger version (44K): org.highwire.dtl.DTLVardef@1de7f42org.highwire.dtl.DTLVardef@74e8ddorg.highwire.dtl.DTLVardef@1642847org.highwire.dtl.DTLVardef@907a23_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 5C_FLOATNO Distinct pre-cancer signs in epithelial and immune cells of LS para-carcinoma (A) The scRNA-seq datasets of LS-paraCA were integrated with those of the colons from healthy donors (HD) (N=3, respectively; the HD group had 7885 cells in total, whereas the LS-paraCA group had 4766 cells). A dominance of CEACAM5high epithelial cells were identified in LS-paraCA. The sample from the patient with relapsed LS is marked with an arrow in the bar plot (left panel). (B) The portion of CEACAM5high epithelial cells, infiltrated CD8_T cells and macrophages was quantified. The sample from the relapsed LS patient is marked with arrows. (C, E) Top marker genes co-expressed in CEACAM5high epithelial cells and the enriched pathways are illustrated in the gene expression heatmap. Cells from the Enterocytes, Tufts, and Goblet subtypes were used as controls. (D, F) Quantification of the expression of CEACAM5 in epithelial cells of HD and LS-paraCA cells. C_FIG O_FIG O_LINKSMALLFIG WIDTH=178 HEIGHT=200 SRC="FIGDIR/small/647495v1_fig3.gif" ALT="Figure 3"> View larger version (48K): org.highwire.dtl.DTLVardef@142c991org.highwire.dtl.DTLVardef@1bf5d99org.highwire.dtl.DTLVardef@99edd5org.highwire.dtl.DTLVardef@1cd5c15_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 3C_FLOATNO Distinct infiltration of immune cells in carcinoma and para-carcinoma tissues of LS (A) Fresh paired carcinoma (LS-CA) and adjacent para-carcinoma (LS-paraCA) biopsies of colon tissue was subjected to scRNA-seq analysis (N=3). Colorectal cancer (nonLS-CRC, they are not diagnosed as LS) tumor samples from the public dataset were also included as controls (N=4). Cells were first grossly annotated as stromal, epithelial, or immune cells. Note that the LS-CA group showed increased infiltration of myeloid cells compared with LS-paraCA group, but T cell infiltration was comparable between the two groups. (B) Expression of classic markers for annotating the major 5 cell types. (C) Detailed annotations of 16 cell types in paired LS-CA and LS-paraCA samples. (D) Stacked bar plot showing the contribution of sample sources in each cell type. (E) Quantification of immune cell infiltration in LS-CA compared with LS-paraCA. Although no significant differences were observed, the fold-changes were approximately 2-10. Although the overall T cell infiltration was comparable, infiltration of GZMA+CD8_T and GZMK+CD8_T cells appeared to be higher in LS-CA than in LS-paraCA. Of the three LS patients enrolled in the study, one was a relapsed patient (gray dashed line, surgery treatment performed; whose son donated the frozen sample in Figure 2), while the other two were treatment-naive (gray solid lines). (F) Boxplots show DNA repair score quantification per sample (above) or per epi-cell. (bottom). C_FIG O_FIG O_LINKSMALLFIG WIDTH=152 HEIGHT=200 SRC="FIGDIR/small/647495v1_fig4.gif" ALT="Figure 4"> View larger version (51K): org.highwire.dtl.DTLVardef@1588458org.highwire.dtl.DTLVardef@58db3borg.highwire.dtl.DTLVardef@1a12084org.highwire.dtl.DTLVardef@15de70e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 4C_FLOATNO Prioritizing novel epithelial biomarkers for tracing the transition between para-carcinoma and carcinoma in LS (LS-paraCA vs. LS-CA) (A) Epithelial cells were filtered out for further analysis and annotated as clusters 0-9 in the UMAP plot. (B, C) Bar and pie plots show the contribution of sources to epithelial clusters. Cluster 0 contained cells largely from Lynch CA_02, whereas Cluster 9 was composed of Lynch paraCA_02. The patient who donated Lynch CA_02 and paraCA_02 is identified as a relapsed LS. (D) KEGG enrichment analysis showing the enriched bioprocesses in the four epithelial cell clusters. (E) Five genes with upregulated expression in LS carcinoma epithelial cells were prioritized based on the scRNA-seq and snRNA-seq datasets. (F) Expression of BACE2, GPRC5A and OLFM4 in the paired LS-paraCA and LS-CA groups. Epithelial cells are circled by dashed lines. Note that the expression of genes in epithelial cells from nonLS-CRC samples was also very strong. (G) Verification of the low-to-high transition in the expression of BACE2, GPRC5A and OLFM4. Paraffin sections from paired LS-paraCA and LS-CA samples were prepared, and immunohistochemical (IHF) staining was performed. The expression of the indicated proteins is labeled in green, whereas the nuclei are stained with DAPI in blue. In total, biopsy samples from 4 patients with LS were used for IHF verification. C_FIG O_FIG O_LINKSMALLFIG WIDTH=148 HEIGHT=200 SRC="FIGDIR/small/647495v1_fig6.gif" ALT="Figure 6"> View larger version (28K): org.highwire.dtl.DTLVardef@1ec5210org.highwire.dtl.DTLVardef@1ffd6f9org.highwire.dtl.DTLVardef@17a7a8forg.highwire.dtl.DTLVardef@4819e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 6C_FLOATNO Increased mutation burden in the colon tissues from Lynch Syndrome (A) The schematic diagram for calculating mutation burden based on the scRNA-seq datasets using the SComatic algorithm. Only single-base substitutions (SBS) were called in this study. Once mutation calls were achieved, the mutation burden value was quantified by normalizing the total mutation calls to the total cell number in the samples or cell types (See Methods section for details). (B) The total SBS mutation burden in the four groups of samples was indicated. (C) The six different SBS mutation burdens in the four groups of samples as indicated. (D) The SBS mutation burden in the cell types of the four groups is indicated. Note that the The mutation burden appears to be higher in mast, epithelial, plasma, myeloid, and Treg cells in the LS-CA group than in that the LS-paraCA group. C_FIG

cancer biology↗

Brucella proline racemase protein A targets Tpl2 to promote IL-10 secretion for establishment of chronic infection

IL-10, an anti-inflammatory cytokine, plays a crucial role in limiting immune responses to pathogens, preventing host damage. However, the mechanisms underlying Brucella-mediated IL- 10 production remain incompletely understood. In this study, we demonstrate that the proline racemase protein A (PrpA) of Brucella melitensis M5-90 induces macrophages to secrete IL-10 by activating the Tpl2-ERK signaling pathway, thereby promoting chronic infection. Moreover, Tpl2 deletion impairs macrophage bactericidal ability, accompanied by reduced TNF- and IL-1{beta} but unaffected IL-10 levels. Additionally, Trp309, Glu103, and Glu129 of PrpA participate in interaction with Tpl2, but these residues do not influence PrpA-mediated IL-10 production in macrophages. PrpA deletion enhances IFN-{gamma} levels, specific anti-Brucella IgG, and CD4+ and CD8+ T cell numbers in mice. Furthermore, the Brucella melitensis M5-90 prpA mutant provides higher protection than the parental strain against virulent Brucella melitensis M28 infection in mice. Our findings suggest that Brucella PrpA promotes IL-10 secretion by macrophages through Tpl2 activation for bacterial survival and persistent infection, making the Brucella melitensis M5-90 prpA mutant a promising vaccine for enhanced protection. Author SummaryIL-10, an anti-inflammatory cytokine, is exploited by Brucella for survival. We identified Brucella PrpA as a potent IL-10 inducer, activating the Tpl2-ERK signaling pathway. Tpl2 deletion increased Brucella survival in macrophages, accompanied by reduced TNF- and IL-1{beta} but unaffected IL-10 secretion. Residues (Trp309, Glu103, and Glu129) of PrpA were crucial for interaction with Tpl2, yet did not impact PrpA-mediated IL-10 production. The B. melitensis M5-90 prpA mutant induced higher anti-Brucella IgG, IFN-{gamma}, and CD4+ and CD8+ T cell numbers in mice, providing better protection than B. melitensis M5-90. These findings unveil PrpAs role in IL-10 production and highlight the potential of the B. melitensis M5-90 prpA mutant as a promising vaccine for further evaluation.

microbiology↗

Top-down attention and Alzheimer's pathology impact cortical selectivity during learning,influencing episodic memory in older adults

Human aging affects the ability to remember new experiences, in part, because of altered neural function during memory formation. One potential contributor to age-related memory decline is diminished neural selectivity -- i.e., a decline in the differential response of cortical regions to preferred vs. non-preferred stimuli during event perception -- yet the factors driving variability in neural selectivity with age remain unclear. We examined the impact of top-down attention and preclinical Alzheimers disease (AD) pathology on neural selectivity during memory encoding in 156 cognitively unimpaired older participants who underwent fMRI while performing a word-face and word-scene associative memory task. Neural selectivity in face- and place-selective cortical regions was greater during events that were later remembered compared to forgotten. Critically, neural selectivity during learning positively scaled with memory-related variability in top-down attention, whereas selectivity negatively related to early AD pathology, evidenced by elevated plasma pTau181. Path analysis revealed that neural selectivity at encoding mediated the effects of age, top-down attention, and pTau181 on associative memory. Collectively, these data reveal multiple pathways that contribute to memory differences among older adults -- AD-independent reductions in top-down attention and AD-related pathology alter the precision of cortical representations of events during experience, with consequences for remembering.

neuroscience↗

VAPOR: Variational autoencoder with transport operators decouples co-occurring biological processes in development

Abstract Single-cell and spatial transcriptomics enable the analysis of cellular states and dynamics in gene expression, revealing how diverse biological processes relate to these states over time and space. To study these dynamics, trajectory inference methods order cells along computationally inferred paths to reconstruct gradual transitions in cell states. However, by encouraging smooth and continuous trajectories, these approaches tend to conflate co-occurring processes-such as proliferation, maturation, and spatial organization-that are jointly reflected in gene expression, potentially overlooking process-specific gene expression dynamics. To address this, we developed VAPOR, which integrates a variational autoencoder with transport operators to model and disentangle cellular gene expression dynamics for potentially co-occurring biological processes. VAPOR inputs single-cell (or spatial) gene expression data into a variational autoencoder (VAE) to learn the latent states of cells and then models their latent dynamics as an ordinary differential equation. The latent dynamics are further decomposed into process-specific components parameterized by transport operators (TOs) and their corresponding process weights. Each TO defines a process-specific dynamics, and its weight for each cell quantifies the process's contribution to the cell dynamics. After assessment by simulation studies, we applied VAPOR with benchmarking to real data, including time-course scRNA-seq from postconceptual human brain development, spatial transcriptomics of the mouse hippocampus, and cross-species scRNA-seq spanning human and macaque first-trimester forebrain development. In these applications, VAPOR has identified a variety of temporal and spatial co-occurring processes, such as cell cycle, gliogenesis, neurogenesis, and neuronal migration, along with associated dynamic genes, including those species-specific to human and macaque development. VAPOR is available as an open-source tool for general-purpose use.

bioinformatics↗

The stability of lower genital tract microbiota correlates with reproductive system function and in vitro fertilization and frozen embryo transfer outcomes in women with polycystic ovarian syndrome

We previously found that the lower genital tract (LGT) microbiota of polycystic ovarian syndrome (PCOS) women has altered when compared to healthy reproductive-aged women, however whether this alternation will have an impact on the reproductive system function and pregnancy outcomes of PCOS patients have not yet been identified. Between 2018 and 2021, we totally enrolled 191 reproductive-aged women in three independent case-control studies, 209 vaginal and 209 cervical swabs, and 9 cervical epithelial cells samples were collected from the study subjects. Firstly, we analyzed the correlation between LGT flora and clinical characteristics of 97 women (containing 47 PCOS patients and 50 control reproductive-aged women), canonical correspondence analysis (CCA) showed that LH/FSH ratio was the most relevant factor that was related to the dominant genera in women with PCOS (r2=0.233, p=0.001), and menstrual cycle frequency was also strongly related to the LGT organisms (r2=0.116, p=0.005). Next, through analysis of 72 PCOS patients who were underwent IVF-FET therapy, the FET outcome in PNB group (PCOS with relative abundance of Lactobacillus [&ge;]50%, n=57) was significant better than PDB group(PCOS patients with relative abundance of Lactobacillus<50%, n=15). Further, we randomly selected nine reproductive-aged PCOS patients (approximately half of them had altered LGT microbiota: Lactobacillus spp. [&le;]50%, n=5) and simultaneously collected both LGT swabs and cervical epithelial cells from them. By synchronization analysis of RNA sequencing of the cervical epithelial cells and 16S rRNA sequencing of the microbes, we found that the gene expression profiles of the cells significantly differed between the PDB (PCOS patients with relative abundance of Lactobacillus<50%, n=4) and PNB (PCOS with relative abundance of Lactobacillus [&ge;]50%, n=5) groups. Above all, we systematically elucidate the potential relationship between LGT microbiota with the reproductive system function and IVF-FET outcomes in PCOS patients. Importancepolycystic ovarian syndrome (PCOS) women always suffered from poor pregnancy outcome: high incidence of abortion, preterm-birth, and premature rupture of membranes. Although some patients have improved their reproductive outcomes through assisted reproductive technology, the risk of early clinical pregnancy loss for PCOS patients after IVF treatment still ranges from 12% to 48%. As we previously found that the LGT flora of PCOS women had significant altered when compared with healthy parallel group, and more evidence showed that the genital tract microbiota may have a critical role in the process of embryo implantation and development, here we used multiple study groups to explore the potential relationship between LGT microbiota with reproductive system function and FET outcome in PCOS patients in this study. Our findings provide a new perspective for exploring novel therapy to improve the reproductive outcomes of PCOS patients.

physiology↗

Charting Single Cell Lineage Dynamics and Mutation Networks via Homing CRISPR

Single cell lineage tracing, essential for unraveling cellular dynamics in disease evolution is critical for developing targeted therapies. CRISPR-Cas9, known for inducing permanent and cumulative mutations, is a cornerstone in lineage tracing. The novel homing guide RNA (hgRNA) technology enhances this by enabling dynamic retargeting and facilitating ongoing genetic modifications. Charting these mutations, especially through successive hgRNA edits, poses a significant challenge. Our solution, LINEMAP, is a computational framework designed to trace and map these mutations with precision. LINEMAP meticulously discerns mutation alleles at single-cell resolution and maps their complex interrelationships through a mutation evolution network. By utilizing a Markov Process model, we can predict mutation transition probabilities, revealing potential mutational routes and pathways. Our reconstruction algorithm, anchored in the Markov models attributes, reconstructs cellular lineage pathways, shedding light on the cells evolutionary journey to the minutiae of single-cell division. Our findings reveal an intricate network of mutation evolution paired with a predictive Markov model, advancing our capability to reconstruct single-cell lineage via hgRNA. This has substantial implications for advancing our understanding of biological mechanisms and propelling medical research forward.

bioinformatics↗

Decreased fucosylation impacts epithelial integrity and increases risk for COPD.

COPD causes significant morbidity and mortality worldwide. Epithelial damage is fundamental to disease pathogenesis, although the mechanisms driving disease remain undefined. Published evidence from a COPD cohort (SPIROMICS) and confirmed in a second cohort (COPDgene) demonstrate a polymorphism in Fucosyltransferese-2 (FUT2) is a trans-pQTL for E-cadherin, which is critical in COPD pathogenesis. We found by MALDI-TOF analysis that FUT2 increased terminal fucosylation of E-cadherin. Using atomic force microscopy, we found that FUT2-dependent fucosylation enhanced E-cadherin-E-cadherin bond strength, mediating the improvement in monolayer integrity. Tracheal epithelial cells from Fut2-/- mice have reduced epithelial integrity, which is recovered with reconstitution of Fut2. Overexpression of FUT2 in COPD derived epithelia rescues barrier function. Fut2-/- mice show increased susceptibility in an elastase model of disease developing both emphysema and fibrosis. We propose this is due to the role of FUT2 in proliferation and cell differentiation. Overexpression of FUT2 significantly increased proliferation. Loss of Fut2 results in accumulation of Spc+ cells suggesting a failure of alveolar type 2 cells to undergo transdifferentiation to alveolar type 1. Using a combination of population data, genetically manipulated mouse models, and patient-derived cells, we present a novel mechanism by which post-translational modifications modulate tissue pathology and serve as a proof of concept for the development of a disease-modifying target in COPD.

cell biology↗