Biology subjects

Hou, W.

Publications and source records attributed to Hou, W..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Different Roles of D1/D2 Medium Spiny Neurons in the Nucleus Accumbens in Pair Bond Formation of Male Mandarin Voles

The mesolimbic dopamine (DA) system has been implicated in pair bond formation. However, involvements of DA release, real time activities, and electrophysiological activities of D1/D2 medium spiny neurons (MSNs) in the nucleus accumbens (NAc) shell in pair bonding remain unclear. This work verified that male mandarin voles after pair bonding released higher levels of DA in the NAc shell and displayed higher levels of D1 MSNs activity and lower levels of D2 MSNs activity upon sniffing their partners compared to upon sniffing an unknown female. Moreover, pair bonding induced differential alterations in both synaptic plasticity and neuronal intrinsic excitability in both D1 MSNs and D2 MSNs. In addition, chemogenetic inhibition of ventral pallidum (VP) -projecting D2 MSNs in the NAc shell enhanced pair bond formation, while chemogenetic activation of VP-projecting D2 MSNs in the NAc shell inhibited pair bond formation. These findings suggest that different neuronal activity of NAc shell D1 MSNs / D2 MSNs regulated by increasing DA release after pair bonding may be a neurobiological mechanism underlying pair bond formation.

neuroscience↗

bioRxiv2024

PVN-mPFC OT projections modulates pup-directed pup care or attacking in virgin mandarin voles

In many species, adult animals may exhibit caregiving or aggression towards conspecific offspring. The neural mechanisms underlying the infanticide and pup care remain poorly understood. Here, using monogamous virgin mandarin voles (Microtus mandarinus) that may exhibit pup care or infanticide, we found that more oxytocin (OT) neurons in the paraventricular nucleus (PVN) were activated during pup caring than infanticide. Optogenetic activation of OT neurons in the PVN facilitated pup-caring in male and female mandarin voles. In infanticide voles, optogenetic activation of PVN OT cells prolonged latency to approach and attack pups, whereas inhibition of these OT neurons facilitated approach and infanticide. In addition, OT release in the medial prefrontal cortex (mPFC) in pup-care voles increased upon approaching and retrieving pups, and decreased in infanticide voles upon attacking pups. Optogenetic activation of PVN OT neuron projections to the mPFC shortened the latency to approach and retrieve pups and facilitated the initiation of pup care, whereas inhibition of these projections had little effect. For pup-care females, neither activation nor inhibition of the fibers affected their behavior towards pups. In infanticide male and female voles, optogenetic activation of PVN-mPFC OT projection fibers prolonged the latency to approach and attack pups and suppressed the initiation of infanticide, whereas inhibition of these projections promoted approach and infanticide. Finally, we found that intraperitoneal injection of OT promoted pup care and inhibited infanticide behavior. It is suggested that the OT system, especially PVN OT neurons projecting to mPFC, modulates pup-directed behaviors and OT can be used to treat abnormal behavioral responses associated with some psychological diseases such as depression and psychosis.

neuroscience↗

bioRxiv2024

GPT-4V exhibits human-like performance in biomedical image classification

Image classification plays a pivotal role in analyzing biomedical images, serving as a cornerstone for both biological research and clinical diagnostics. We demonstrate that large multimodal models (LMMs), like GPT-4, excel in one-shot learning, generalization, interpretability, and text-driven image classification across diverse biomedical tasks. These tasks include the classification of tissues, cell types, cellular states, and disease status. LMMs stand out from traditional single-modal classification approaches, which often require large training datasets and offer limited interpretability.

bioinformatics↗

bioRxiv2023

Toward Best Practice in Identifying Subtle Differential Expression with RNA-seq: A Real-World Multi-Center Benchmarking Study Using Quartet and MAQC Reference Materials

Translating RNA-seq into clinical diagnostics requires ensuring the reliability of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. Moreover, cross-laboratory reproducibility and consistency under diverse experimental and bioinformatics workflows urgently need to be addressed. As part of the Quartet project, we presented a comprehensive RNA-seq benchmarking study utilizing Quartet and MAQC RNA reference samples spiked with ERCC controls in 45 independent laboratories, each employing their in-house RNA-seq workflows. We assessed the data quality, accuracy and reproducibility of gene expression and differential gene expression and compared over 40 experimental processes and 140 combined differential analysis pipelines based on multiple ground truths. Here we show that real-world RNA-seq exhibited greater inter-laboratory variations when detecting subtle differential expressions between Quartet samples. Experimental factors including mRNA enrichment methods and strandedness, and each bioinformatics step, particularly normalization, emerged as primary sources of variations in gene expression and have a more pronounced impact on the subtle differential expression measurement. We underscored the pivotal role of experimental execution over the choice of experimental protocols, the importance of strategies for filtering low-expression genes, and optimal gene annotation and analysis tools. In summary, this study provided best practice recommendations for the development, optimization, and quality control of RNA-seq for clinical diagnostic purposes.

genomics↗

bioRxiv2023

Modern wheat breeding selection synergistically improves above- and below-ground traits

The root system, as a fundamental organ for uptaking water and nutrients and interacting with the local environmental conditions, has been postulated to be the foundation for a second Green Revolution. However, the status of the root system during modern wheat breeding remains to be elucidated. Here, by analyzing the phenotypes of 406 wheat accessions on a large scale, we found the root systems of modern cultivars were synchronisely changed along with the above-ground traits. Furthermore, the genomic blocks with phenotypic effects on both above- and below-ground traits were observed to be enriched in the selection sweeps, highlighting that modern wheat breeding contributed to the synchronised changes. More importantly, the haplotypes selected by breeders within the selection sweeps synergistically improved both the above- and below-ground traits, suggesting that modern wheat breeding has improved the root system indirectly, which may contribute to the higher grain yields of modern wheat cultivars. Our results demonstrated that modern wheat breeding synergistically improved the above- and below-ground traits.

genetics↗

bioRxiv2023

Biochemical and functional characterization of the p.A165T missense variant of mitochondrial amidoxime-reducing component 1 in HepG2 cells

Recent genome-wide association studies have identified a missense variant p.A165T in mitochondrial amidoxime-reducing component 1 (mARC1) that is strongly associated with protection from all-cause cirrhosis and improved prognosis in nonalcoholic steatohepatitis (NASH). The precise mechanism of this protective effect is unknown. Substitution of alanine 165 with threonine is predicted to affect mARC1 protein stability and to have deleterious effects on its function. To investigate the mechanism, we have generated a knock-in mutant mARC1 A165T in human hepatoma HepG2 cells, enabling characterization of protein subcellular distribution, stability, and biochemical functions of the mARC1 mutant protein expressed from its endogenous locus. Compared to wild-type (WT) mARC1, we found that the A165T mutant exhibits significant mislocalization outside of its traditional location anchored in the mitochondrial outer membrane and reduces protein stability, resulting in lower basal levels. We evaluated the involvement of the ubiquitin proteasome system in mARC1 A165T degradation and observed increased ubiquitination and faster degradation of the A165T variant. In addition, we have shown that HepG2 cells carrying the MTARC1 p.A165T variant exhibit lower N-reductive activity on exogenously-added amidoxime substrates in vitro. The data from these biochemical and functional assays suggest a mechanism by which the MTARC1 p.A165T variant abrogates enzyme function which may contribute to its protective effect in liver disease.

cell biology↗

bioRxiv2023

Plasma-free samples for transcriptomic analysis: a potential alternative to whole blood samples

RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the viability of employing PFB or SFB samples as substitute RNA sources in transcriptomic analysis and performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples in terms of protein-coding gene expression patterns, differential expression gene profiling, and immunological characterizations, suggesting that PFB can be a viable alternative for transcriptomic analysis. This contributes to the optimization of blood sample utilization and the advancement of precision medicine research.

bioinformatics↗

bioRxiv2023

Reference-free and cost-effective automated cell type annotation with GPT-4 in single-cell RNA-seq analysis

Cell type annotation is an essential step in single-cell RNA-seq analysis. However, it is a time-consuming process that often requires expertise in collecting canonical marker genes and manually annotating cell types. Automated cell type annotation methods typically require the acquisition of high-quality reference datasets and the development of additional pipelines. We assessed the performance of GPT-4, a highly potent large language model, for cell type annotation, and demonstrated that it can automatically and accurately annotate cell types by utilizing marker gene information generated from standard single-cell RNA-seq analysis pipelines. Evaluated across hundreds of tissue types and cell types, GPT-4 generates cell type annotations exhibiting strong concordance with manual annotations and has the potential to considerably reduce the effort and expertise needed in cell type annotation. We also developed GPTCelltype, an open-source R software package to facilitate cell type annotation by GPT-4.

bioinformatics↗

bioRxiv2023

Distinct Myeloid Derived Suppressor Cell Populations Promote Tumor Aggression in Glioblastoma

The diversity of genetic programs and cellular plasticity of glioma-associated myeloid cells, and thus their contribution to tumor growth and immune evasion, is poorly understood. We performed single cell RNA-sequencing of immune and tumor cells from 33 glioma patients of varying tumor grades. We identified two populations characteristic of myeloid derived suppressor cells (MDSC), unique to glioblastoma (GBM) and absent in grades II and III tumors: i) an early progenitor population (E-MDSC) characterized by strong upregulation of multiple catabolic, anabolic, oxidative stress, and hypoxia pathways typically observed within tumor cells themselves, and ii) a monocytic MDSC (M-MDSC) population. The E-MDSCs geographically co-localize with a subset of highly metabolic glioma stem-like tumor cells with a mesenchymal program in the pseudopalisading region, a pathognomonic feature of GBMs associated with poor prognosis. Ligand-receptor interaction analysis revealed symbiotic cross-talk between the stemlike tumor cells and E-MDSCs in GBM, whereby glioma stem cells produce chemokines attracting E-MDSCs, which in turn produce growth and survival factors for the tumor cells. Our large-scale single-cell analysis elucidated unique MDSC populations as key facilitators of GBM progression and mediators of tumor immunosuppression, suggesting that targeting these specific myeloid compartments, including their metabolic programs, may be a promising therapeutic intervention in this deadly cancer. One-Sentence SummaryAggressive glioblastoma harbors two unique myeloid populations capable of promoting stem-like properties of tumor cells and suppressing T cell function in the tumor microenvironment.

immunology↗

bioRxiv2023

Quantification of elongation stalls and impact on gene expression in yeast

Ribosomal pauses are a critical part of co-translational events including protein folding and localization. However, extended ribosome pauses can lead to ribosome collisions, resulting in the activation of ribosome rescue pathways and turnover of protein and mRNA. While this relationship has been known, the specific threshold between permissible pausing versus activation of rescue pathways has not been quantified. We have taken a method used to measure elongation time and adapted it for use in S. cerevisiae to quantify the impact of elongation stalls. We find, in transcripts containing Arg CGA codon repeat-induced stalls, a Hel2-mediated dose-dependent decrease in protein expression and mRNA level and an elongation delay on the order of minutes. In transcripts that contain synonymous substitutions to non-optimal Leu codons, there is a decrease in protein and mRNA levels, as well as similar elongation delay, but this occurs through a non-Hel2-mediated mechanism. Finally, we find that Dhh1 selectively increases protein expression, mRNA level, and elongation rate. This indicates that distinct poorly translated codons in an mRNA will activate different rescue pathways despite similar elongation stall durations. Taken together, these results provide new quantitative mechanistic insight into the surveillance of translation and the roles of Hel2 and Dhh1 in mediating ribosome pausing events.

molecular biology↗

bioRxiv2023

GeneTuring tests GPT models in genomics

Large language models (LLMs) show promise in biomedical research, but their effectiveness for genomic inquiry remains unclear. We developed GeneTuring, a benchmark consisting of 16 genomics tasks with 1,600 curated questions, and manually evaluated 48,000 answers from ten LLM configurations, including GPT-4o (via API, ChatGPT with web access, and a custom GPT setup), GPT-3.5, Claude 3.5, Gemini Advanced, GeneGPT (both slim and full), BioGPT, and BioMedLM. A custom GPT-4o configuration integrated with NCBI APIs, developed in this study as SeqSnap, achieved the best overall performance. GPT-4o with web access and GeneGPT demonstrated complementary strengths. Our findings highlight both the promise and current limitations of LLMs in genomics, and emphasize the value of combining LLMs with domain-specific tools for robust genomic intelligence. GeneTuring offers a key resource for benchmarking and improving LLMs in biomedical research. Biographical NoteDr. Wenpin Hou is an Assistant Professor (tenure-track) in the Department of Biostatistics at Columbia University and member of its Data Science Institute, developing AI and statistical methods for decoding gene regulatory programs from single-cell and spatial multiomics data.

bioinformatics↗

bioRxiv2022

GeneSegNet: A deep learning framework for cell segmentation by integrating gene expression and imaging

When analyzing data from in situ RNA detection technologies, cell segmentation is an essential step in identifying cell boundaries, assigning RNA reads to cells, and studying the gene expression and morphological features of cells. We developed a deep-learning-based method, GeneSegNet, that integrates both gene expression and imaging information to perform cell segmentation. GeneSegNet also employs a recursive training strategy to deal with noisy training labels. We show that GeneSegNet significantly improves cell segmentation performances over existing methods that either ignore gene expression information or underutilize imaging information.

bioinformatics↗

bioRxiv2022

Lung tumor-infiltrating Treg have divergent transcriptional profiles and function linked to checkpoint blockade response

Regulatory T cells (Treg) are conventionally viewed to suppress endogenous and therapyinduced anti-tumor immunity; however, their role in modulating responses to immune checkpoint blockade (ICB) is unclear. In this study, we integrated single-cell RNAseq/TCRseq of >73,000 tumor-infiltrating Treg (TIL-Treg) from anti-PD-1-treated and treatment naive non-small cell lung cancers (NSCLC) with single cell analysis of tumor-associated antigen (TAA)-specific Treg derived from a murine tumor model. We identified 10 subsets of human TIL-Treg, most of which have high concordance with murine TIL-Treg subsets. Notably, one subset selectively expresses high levels of OX40 and GITR, whose engangement by cognate ligand mediated proliferative programs and NF-kB activation, as well as multiple genes involved in Treg suppression, in particular LAG3. Functionally, the OX40hiGITRhi subset in the most highly suppressive ex vivo and Treg expression of OX40, GITR and LAG3, correlated with resistance to PD-1 blockade. Surprisingly, in the murine tumor model, we found that virtually all TIL-Treg expressing T cell receptors that are specific for TAA fully develop a distinct Th1-like signature over a two-week period after entry into the tumor, down-regulating FoxP3 and up-regulating expression of TBX21 (Tbet), IFN{gamma} and certain pro-inflammatory granzymes. Application of a gene score from the murine TAA-specific Th1-like Treg subset to the human single-cell dataset revealed a highly analogous subcluster that was enriched in anti-PD-1 responding tumors. These findings demonstrate that TIL-Treg partition into multiple distinct transcriptionally-defined subsets with potentially opposing effects on ICB-induced anti-tumor immunity and suggest that TAA-specific TIL-Treg may positively contribute to anti-tumor responses. One-Sentence SummaryWe define 10 subsets of lung cancer-infiltrating regulatory T cells, one of which is highly suppressive and enriched in anti-PD-1 non-responders and the other is Th1-like and is enriched in PD-1 responders.

immunology↗

bioRxiv2022

Transcription-independent hold of the G1/S transition is exploited to cope with DNA replication stress

RB1 (retinoblastoma) members control the G1/S commitment as transcriptional repressors in eukaryotic cells. Here we uncover that an extra copy of RB1 equivalent (WHI7 or WHI5) is sufficient to bypass the indispensability of the central genomic checkpoint kinases Mec1ATR-Rad53CHK1 in Saccharomyces cerevisiae. Mec1-Rad53 directly phosphorylate Whi7/5, antagonizing their nuclear export or protein turnover upon replication stress. Through in vitro reconstitution, we show that Whi7 C-terminus directly binds and hinders S-CDK-Cks1 from processively phosphorylating Sic1. By microfluidic single-cell real-time quantitative imaging, we demonstrate that both Whi7 and Whi5 are required to flatten the degradation curve of the major S-CDK inhibitor Sic1 in vivo. These findings reveal an eclipsed transcription-independent role of Whi7 homologs, which is highlighted by genome integrity checkpoints to hold the G1/S transition instantly as a rapid response to unforeseeable replication threats. Key pointsO_LIWhi7 overexpression bypasses the essential function of Mec1 and Rad53 in a transcription-independent way. C_LIO_LIWhi7 is stabilized by checkpoint-mediated phosphorylation. C_LIO_LIWhi7 binds and hinders S-CDK-Cks1 from multi-phosphorylation of Sci1, thereby prolonging Sic1 degradation and G1/S transition. C_LI

molecular biology↗

bioRxiv2022

Quartet metabolite reference materials for assessing inter-laboratory reliability and data integration of metabolomic profiling

Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets. As part of the Quartet Project, we established a publicly available suite of four metabolite reference materials derived from B-lymphoblastoid cell lines from a family quartet of parents and monozygotic twin daughters. We generated comprehensive LC-MS based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. High variabilities in the qualitative and quantitative metabolomic measurements were observed across laboratories. Moreover, the Quartet multi-sample-based quality metrics were developed for objectively assessing the reliability of metabolomic profiling in detecting intrinsic biological differences among difference groups of samples. Importantly, the ratio-based metabolomic profiling, by scaling the absolute values of a study sample relative to those of a universal reference sample, enables data integration in long-term measurements across difference laboratories or platforms. Thus, we constructed the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory proficiency test, which enables objective assessment of various metabolomic methods. Our study provided the community with rich resources and best practice for objective assessment of inter-laboratory measurements and data integration, ensuring reliable large-scale and longitudinal metabolomic profiling.

systems biology↗

bioRxiv2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

systems biology↗

bioRxiv2022

Correcting batch effects in large-scale multiomic studies using a reference-material-based ratio method

Batch effects are notorious technical variations that are common in multiomic data and may result in misleading outcomes. With the era of big data, tackling batch effects in multiomic integration is urgently needed. As part of the Quartet Project for quality control and data integration of multiomic profiling, we comprehensively assess the performances of seven batch-effect correction algorithms (BECAs) for mitigating the negative impact of batch effects in multiomic datasets, including transcriptomics, proteomics, and metabolomics. Performances are evaluated based on accuracy of identifying differentially expressed features, robustness of predictive models, and the ability of accurately clustering cross-batch samples into their biological sample groups. Ratio-based method is more effective and widely applicable than others, especially in cases when batch effects are highly confounded with biological factors of interests. We further provide practical guidelines for the implementation of ratio-based method using universal reference materials profiled with study samples. Our findings show the promise for eliminating batch effects and enhancing data integration in increasingly large-scale, cross-batch multiomic studies.

systems biology↗

bioRxiv2022

Quartet DNA reference materials and datasets for comprehensively evaluating germline variants calling performance

Current methods for evaluating the accuracy of germline variant calls are restricted to easy-to-detect high-confidence regions, thus ignoring a substantial portion of difficult variants beyond the benchmark regions. We established four DNA reference materials from immortalized cell lines derived from a Chinese Quartet including parents and monozygotic twins. We integrated benchmark calls of 4.2 million small variants and 15,000 structural variants from multiple platforms and bioinformatic pipelines for evaluating the reliability of germline variant calls inside the benchmark regions. The genetic built-in-truth of the Quartet family design not only improved sensitivity of benchmark calls by removing additional false positive variants with apparently high quality, but also enabled estimation of the precision of variants calls outside the benchmark regions. Batch effects of variant calling in large-scale DNA sequencing efforts can be effectively identified with the concurrent use of the Quartet DNA reference materials along with study samples, and can be alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Matched RNA and protein reference materials were also established in the Quartet project, thereby enabling benchmark calls constructed from DNA reference materials for evaluation of variants calling performance on RNA and protein data. The Quartet DNA reference materials from this study are a resource for objective and comprehensive assessment of the accuracy of germline variant calls throughout the whole-genome regions.

bioinformatics↗