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Sun, S.

Publications and source records attributed to Sun, S..

At least 235 records · Page 13Linked to original sources

DeepHeme: A generalizable, bone marrow classifierwith hematopathologist-level performance

Morphology-based classification of cells in the bone marrow aspirate (BMA) is a key step in the diagnosis and management of hematologic malignancies. However, it is time-intensive and must be performed by expert hematopathologists and laboratory professionals. We curated a large, high-quality dataset of 41,595 hematopathologist consensus-annotated single-cell images extracted from BMA whole slide images (WSIs) containing 23 morphologic classes from the clinical archives of the University of California, San Francisco. We trained a convolutional neural network, DeepHeme, to classify images in this dataset, achieving a mean area under the curve (AUC) of 0.99. DeepHeme was then externally validated on WSIs from Memorial Sloan Kettering Cancer Center, with a similar AUC of 0.98, demonstrating robust generalization. When compared to individual hematopathologists from three different top academic medical centers, the algorithm outperformed all three. Finally, DeepHeme reliably identified cell states such as mitosis, paving the way for image-based quantification of mitotic index in a cell-specific manner, which may have important clinical applications.

bioinformatics↗

Improved in situ Characterization of Proteome-wide Protein Complex Dynamics with Thermal Proximity Co-Aggregation

Vast majority of cellular activities are carried out by protein complexes that assembled dynamically in response to cellular needs and environmental cues. Large scale efforts had uncovered a large repertoire of functionally uncharacterized protein complexes which necessitate new strategies to delineate their roles in various cellular activities and diseases. Thermal proximity co-aggregation profiling could be readily deployed to simultaneously characterize the dynamics for hundreds to thousands of protein complexes in situ across different cellular conditions. Toward this goal, we had optimized the original method both experimentally and computationally. In this new iteration termed Slim-TPCA, fewer temperatures are used which increase throughputs by over 3X, while coupled with new scoring metrics and statistical evaluation resulted in minimal compromise in coverage and the detection of more relevant protein complexes. Overall, less samples are needed, false positives from batch effects are minimized and statistical evaluation time is reduced by two orders of magnitude. We applied Slim-TPCA to profile state of protein complexes in K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated based on TPCA signature in accordance with expected downregulation of most cellular activities. These complexes include 55S ribosome and various respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. On other hand, protein complexes involved in protein transport and degradation are found increasingly associated revealing their involvement in metabolic reprogramming during glucose deprivation. In summary. Slim-TPCA is an efficient strategy for proteome-wide characterization of protein complexes. The various algorithmic improvement of Slim-TPCA is available as Python package at https://pypi.org/project/Slim-TPCA/

bioinformatics↗

The effect of glucagon-like peptide-1 receptor agonist (GLP1RA) on hypertensive-induced heart failure with preserved ejection fraction and hypertensive cardiomyopathy

Emerging preclinical data suggest that glucagon-like peptide-1 receptor agonist (GLP1RA) possesses cardioprotective properties against the pathophysiology of hypertension (HT). We sought to unravel the potential therapeutic application of GLP1RA in a clinically relevant large animal model of hypertensive cardiomyopathy (hCMP). A combination of angiotensin II (Ang II) and deoxycorticosterone acetate (DOCA) pellets were used to induce sustained HT status and establish hCMP in porcine model. Changes in cardiac echocardiography, invasive hemodynamic parameters, neurohumoral biomarkers and inflammation-related cytokines were investigated in 23 adult pigs, among which 6 were serving as control, 9 were induced with HT, and the remaining 8 were HT-induced with GLP1RA treatment. Eight weeks after the study initiated, HT pigs have developed sustained high blood pressure (BP) at both systole and diastole. Phenotype of hCMP has also become significant as impairment in systolic/diastolic function, left ventricular remodeling and cardiac hypertrophy was determined by echocardiogram and invasive hemodynamics. Additionally, blood norepinephrine (NE) content, venoarterial NE gradient and pro-inflammatory cytokines in HT pigs were increased. GLP1RA treatment halted the elevation in BP, left ventricular remodeling and cardiac hypertrophy development; preserved the left ventricular systolic/diastolic function; reduced the venoarterial NE gradient as well as the pro-inflammatory cytokines at 18 weeks in pigs with hCMP. Our results demonstrate that GLP1RA treatment has a remarkable effect on BP decrease, inflammation suppression and left ventricular function improvement. Thus, we provide novel insight into the therapeutic potential of GLP1RA in HT-induced heart failure in a large animal model of hCMP.

physiology↗

Syntaxin of plants 32 regulates pollen wall development and pollen tube cell wall integrity via controlling secretory pathway

Pollen tubes (PTs) elongate in a polar way to deliver sperm cells to the ovule. Pollen wall development and PT cell wall integrity (CWI) maintenance are critical for PT growth and double fertilization. Pollen wall development mainly relies on secretion of exine precursors in tapetum. RALF4/19-ANX/BUPS-MRI and RALF4/19-LRX-AUN are two distinct signaling pathways but converge to fine-tune CWI during PT growth. Here, we discovered that atsyp32+/-, AtSYP32 RNAi and AtSYP3132 RNAi lines were male sterile. The tapetum development in these lines were disturbed, and the pollen wall structure was impaired resulting in pollen grain and tube bursting and less PTs navigated to micropyles. Strikingly, there were numerous ectopic secretory vesicles retained in pollen cytoplasm, and the abundance or distribution of polysaccharides and AGPs altered significantly in PTs of the mutants and RNAi lines. AtSYP32 interacted with the vesicle transport regulators SEC31B, SEC22 and BET12, the PT CWI regulators RALF19 and LRX11, and the XyG xylosyltransferase XXT5, in the Golgi apparatus. Transcription of some genes related to pollen wall biosynthesis and PT CWI maintenance were seriously affected by AtSYP32 downregulation. Our findings illustrate that AtSYP32 plays essential roles in pollen wall development and PT CWI maintenance via controlling secretory pathway. IN A NUTSHELLO_ST_ABSBackgroundC_ST_ABSPollen wall is the most complex cell wall. Pollen wall development mainly relies on secretion of precursors of exine and pollen coat in tapetal cells. Pollen tubes (PTs) grow in a polar way to deliver sperm cells to the ovule. Maintenance of PT cell wall integrity (CWI) is critical for PT elongation and double fertilization. RALF4/19 ligands interact with BUPS-ANX receptors, signaling it in an autocrine manner to maintain CWI during PT elongation. RALF4/19-LRX-AUN pathway is distinct with RALF4/19-ANX/BUPS-MRI pathway but they converge to fine-tune CWI during PT growth. Biosynthesis of PT cell wall involves multiple subcellular compartments and vesicle transport pathways. Golgi apparatus acts as a hub in vesicle trafficking. Golgi-syntaxin AtSYP31 and AtSYP32 regulate pollen development by controlling intra-Golgi transport and Golgi morphology QuestionWhat is AtSYP32 role in pollen wall and tapetum development? Who are the AtSYP32 partners that regulate secretion of cell wall biosynthesis materials? FindingsWe found that no homozygote progeny was obtained from self-pollinated atsyp32+/- alleles due to pollen sterile. The tapetum development and degeneration in atsyp32+/- mutants was severely delayed, and the pollen wall and PT wall structure were impaired. Strikingly, there were numerous ectopic secretory vesicles retained in pollen cytoplasm in atsyp32+/- mutants, and the abundance or distribution of PT wall polysaccharides and AGPs altered obviously. AtSYP32 interacted with the vesicle transport regulators SEC31B, SEC22 and BET12, the PT CWI regulators RALF19 and LRX11, and XyG xylosyltransferase XXT5, in the Golgi. All these highlight that AtSYP32 regulates pollen wall development and maintenance of PT CWI via controlling secretory pathway. Next stepsThe biological significances and the molecular mechanisms of AtSYP32 interacting with XXT5, RALF19 and LRX11 are elusive but thought-provoking. We are going to clarify the mechanisms.

molecular biology↗

Multi-omics Comparison among Populations of Three Plant Sources of Amomi Fructus

Amomi Fructus (Sharen, AF) is a traditional Chinese medicine (TCM) from three source species (or subspecies) including Wurfbainia villosa var. villosa (WVV), W. villosa var. xanthioides (WVX) or W. longiligularis (WL). Among them, WVV has been transplanted from its top-geoherb region Guangdong to its current main production area Yunnan for more than 50 years in China. However, the genetic and transcriptomic differentiation among multiple AF source (sub)species and between the origin and transplanted populations of WVV is unknown. In our study, the observed overall higher expression of terpenoid biosynthesis genes in WVV than that of WVX supplied possible evidence for the better pharmacological effect of WVV. We also screened ten candidate borneol dehydrogenase (BDH) genes that potentially catalyzed borneol into camphor in WVV. The BDH genes may experience independent evolution after acquiring the ancestral copies and the followed tandem duplications might account for the abundant camphor content in WVV. Furthermore, four populations of WVV, WVX and WL are genetically differentiated and the gene flow from WVX to WVV in Yunnan contributed to the increased genetic diversity in the introduced population (WVV-JH) compared to its top-geoherb region (WVV-YC), which showed the lowest genetic diversity and might undergo genetic degradation. In addition, TPS and BDH genes were selected among populations of multiple AF source (sub)species and between the top-geoherb and non-top-geoherb regions, which might explain the metabolite difference of these populations. Our findings provide important guidance for the conservation, genetic improvement, industrial development of the three source (sub)species, and identifying top-geoherbalism with molecular markers and proper clinical application of AF.

evolutionary biology↗

Functional connectivity between the amygdala and prefrontal cortex underlies processing of emotion ambiguity

Processing facial expressions of emotion draws on a distributed brain network. In particular, judging ambiguous facial emotions involves coordination between multiple brain areas. Here, we applied multimodal functional connectivity analysis to achieve network-level understanding of the neural mechanisms underlying perceptual ambiguity in facial expressions. We found directional effective connectivity between the amygdala, dorsomedial prefrontal cortex (dmPFC), and ventromedial PFC, supporting both bottom-up affective processes for ambiguity representation/perception and top-down cognitive processes for ambiguity resolution/decision. Direct recordings from the human neurosurgical patients showed that the responses of amygdala and dmPFC neurons were modulated by the level of emotion ambiguity, and amygdala neurons responded earlier than dmPFC neurons, reflecting the bottom-up process for ambiguity processing. We further found parietal-frontal coherence and delta-alpha cross-frequency coupling involved in encoding emotion ambiguity. We replicated the EEG coherence result using independent experiments and further showed modulation of the coherence. EEG source connectivity revealed that the dmPFC top-down regulated the activities in other brain regions. Lastly, we showed altered behavioral responses in neuropsychiatric patients who may have dysfunctions in amygdala-PFC functional connectivity. Together, using multimodal experimental and analytical approaches, we have delineated a neural network that underlies processing of emotion ambiguity. Significance StatementA large number of different brain regions participate in emotion processing. However, it remains elusive how these brain regions interact and coordinate with each other and collectively encode emotions, especially when the task requires orchestration between different brain areas. In this study, we employed multimodal approaches that well complemented each other to comprehensively study the neural mechanisms of emotion ambiguity. Our results provided a systematic understanding of the amygdala-PFC network underlying emotion ambiguity with fMRI-based connectivity, EEG coordination of cortical regions, synchronization of brain rhythms, directed information flow of the source signals, and latency of single-neuron responses. Our results further shed light on neuropsychiatric patients who have abnormal amygdala-PFC connectivity.

neuroscience↗

Cognitive and neural bases of salience-driven incidental learning

Humans incidentally adjust their behavioral strategies along feedback dimensions even without explicit reasons to do so. How it occurs may depend on stable individual preferences and contextual factors, such as visual salience. We here examined how task-irrelevant visual salience exerts influence on attention and valuation systems that further drives incidental learning. We first established the baseline behavior with no salience emphasis in Exp.1. We then highlighted either the utility or performance dimension of the chosen outcome using colors in Exp.2. We demonstrated that the difference in switching frequency increased along the salient dimension, confirming a strong salience effect. Moreover, the salience effect was abolished when directional information of feedback was removed in Exp.3, suggesting that the observed salience effect is specific to directional feedback. We then generalized our findings using text emphasis in Exp.4 and replicated the non-specific salience effects in Exp.5 with simultaneous eye-tracking. The fixation difference between chosen and unchosen values was enhanced along the feedback-specific salient dimension (Exp.4) but kept unchanged when removing directional information (Exp.5). Moreover, behavioral switching correlates with fixation difference, confirming that salience guides attention and further drives incidental learning. Lastly, our neuroimaging study (Exp.6) showed that the striatum subregions encoded salience-based outcome evaluation, while the vmPFC encoded salience-based behavioral adjustments. The connectivity of the vmPFC-ventral striatum accounted for individual differences in utility-driven, whereas the vmPFC-dmPFC for performance-driven behavioral adjustments. Our results provide a neurocognitive account of how task-irrelevant visual salience drives incidental learning by involving attention and the frontal-striatal valuation systems.

neuroscience↗

Pre-mRNA splicing inhibits m6A deposition, allowing longer mRNA half-life and flexible protein coding

Both pre-mRNA splicing and N6-methyladenosine (m6A) mRNA modification occur during transcription, enabling the potential crosstalk regulation between these two fundamental processes. The regional m6A location bias of avoiding splice site region, calls for an open hypothesis whether pre-mRNA splicing could affect m6A deposition. By deep learning modeling, we find that pre-mRNA splicing represses a proportion (4% to 32%) of m6A deposition at nearby exons. Experimental validation confirms such an inhibition as the m6A signal increases in mRNA once the host gene does not undergo pre-mRNA splicing to produce the same mRNA. Pre-mRNA splicing inhibited m6A sites tend to have higher m6A enhancers and lower m6A silencers locally than the m6A sites that are not inhibited. Moreover, this m6A deposition inhibition by pre-mRNA splicing shows high heterogeneity at different exons of mRNAs at genome-widely, with only a small proportion (12% to 15%) of exons showing strong inhibition, enabling stable mRNAs and flexible protein coding for important biological functions.

genomics↗

Amoeba Predation of Cryptococcus: A Quantitative and Population Genomic Evaluation of the Accidental Pathogen Hypothesis

The "Amoeboid Predator-Fungal Animal Virulence Hypothesis" posits that interactions with environmental phagocytes shape the evolution of virulence traits in fungal pathogens. In this hypothesis, selection to avoid predation by amoeba inadvertently selects for traits that contribute to fungal escape from phagocytic immune cells. Here, we investigate this hypothesis in the human fungal pathogens Cryptococcus neoformans and Cryptococcus deneoformans. Applying quantitative trait locus (QTL) mapping and comparative genomics, we discovered a cross-species QTL region that is responsible for variation in resistance to amoeba predation. In C. neoformans, this same QTL was found to have pleiotropic effects on melanization, an established virulence factor. Through fine mapping and population genomic comparisons, we identified the gene encoding the transcription factor Bzp4 that underlies this pleiotropic QTL and we show that decreased expression of this gene reduces melanization and increases susceptibility to amoeba predation. Despite the joint effects of BZP4 on amoeba resistance and melanin production, we find no relationship between BZP4 genotype and escape from macrophages or virulence in murine models of disease. Our findings provide new perspectives on how microbial ecology shapes the genetic architecture of fungal virulence, and suggests the need for more nuanced models for the evolution of pathogenesis that account for the complexities of both microbe-microbe and microbe-host interactions. Author summaryA prominent hypothesis for the evolution of many environmental pathogens proposes that opportunistic pathogenesis is an "accidental" by-product of selection to survive encounters with microbial predators. Chief among the predators that have been suggested as relevant to the evolution of virulence are phagocytic amoebae. Amoebae share many characteristics with macrophages and other primary immune cells that microbial pathogens encounter during infection of animal hosts. This has led to the suggestion that amoebae may act as "training grounds" for both bacterial and fungal pathogens. In this study we test key tenets of the accidental pathogen hypothesis by examining two related questions: "Do alleles important for survival in the face of amoeba predation correspond to known virulence genes? And does genetic variation that increases resistance to amoeba predation increase virulence potential?" We carried out quantitative trait locus (QTL) mapping in two species of the human fungal pathogen Cryptococcus and identified an orthologous QTL, shared by the two species, where allelic variation is a key predictor of resistance to amoeba predation. In C. neoformans we show that this QTL corresponds to a deletion upstream of a transcription factor gene, BZP4. Variation at BZP4 also predicts melanin synthesis, another trait implicated in Cryptococcus virulence. Although BZP4 genotype is a strong predictor of resistance to amoeba predation, we find no correlation between genetic variation at this locus and the ability to proliferate in macrophages or to kill animal hosts. Our findings suggest that the evolutionary landscape of fungal virulence is complex, and highlights the importance of accounting for natural genetic variation when evaluating evolutionary hypotheses.

genomics↗

Shear and hydrostatic stress regulate fetal heart valve remodeling through YAP-mediated mechanotransduction

Clinically serious congenital heart valve defects arise from improper growth and remodeling of endocardial cushions into leaflets. Genetic mutations have been extensively studied but explain less than 20% of cases. Mechanical forces generated by beating hearts drive valve development, but how these forces collectively determine valve growth and remodeling remains incompletely understood. Here we decouple the influence of those forces on valve size and shape, and study the role of YAP pathway in determining the size and shape. The low oscillatory shear stress promotes YAP nuclear translocation in valvular endothelial cells (VEC), while the high unidirectional shear stress restricts YAP in cytoplasm. The hydrostatic compressive stress activated YAP in valvular interstitial cells (VIC), whereas the tensile stress deactivated YAP. YAP activation by small molecules promoted VIC proliferation and increased valve size. YAP inhibition suppressed the VIC proliferation and reduced valve size, but enhanced cell-cell adhesions between VEC thus maintaining an elongated shape. Finally, left atrial ligation was performed in chick embryonic hearts to manipulate the shear and hydrostatic stress in-vivo. The restricted flow in the left ventricle induced a globular and hypoplastic left atrioventricular (AV) valves with an inhibited YAP expression. By contrast, the right AV valves with sustained YAP expression grew and elongated normally. This study establishes a simple yet elegant mechanobiological system by which transduction of local stresses regulates valve growth and remodeling. This system guides leaflets to grow into proper sizes and shapes with the ventricular development, without the need of a genetically prescribed timing mechanism. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/517814v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@167b319org.highwire.dtl.DTLVardef@11f2f07org.highwire.dtl.DTLVardef@4894f1org.highwire.dtl.DTLVardef@12a66ab_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

Expression of retrotransposons contributes to aging in Drosophila

Retrotransposons are a class of transposable elements capable of self-replication and insertion into new genomic locations. Across species, the mobilization of retrotransposons in somatic cells has been suggested to contribute to the cell and tissue functional decline that occurs during aging. Retrotransposon expression generally increases with age, and de novo insertions have been observed to occur during tumorigenesis. However, the extent to which new retrotransposon insertions occur during normal aging and their effect on cellular and animal function remains understudied. Here we use a single nucleus whole genome sequencing approach in Drosophila to directly test whether transposon insertions increase with age in somatic cells. Analyses of nuclei from thoraces and indirect flight muscles using a newly developed pipeline, Retrofind, revealed no significant increase in the number of transposon insertions with age. Despite this, reducing the expression of two different retrotransposons, 412 and Roo, extends lifespan, without increasing stress resistance. This suggests a key role for transposon expression and not insertion in regulating longevity. Transcriptomic analyses revealed similar changes to gene expression in 412 and Roo knockdown flies and highlighted potential changes to genes involved in proteolysis and immune function as potential contributors to the observed changes in longevity. Combined, our data show a clear link between retrotransposon expression and aging. Author SummaryWith the onset of modern medicine, the average age of the population has significantly increased, leading to more individuals living with chronic health issues. Rather than treat each age-associated disorder individually, one approach to target multiple health concerns simultaneously might to be target aging itself. Genomic instability is a hallmark of aging cells that has been proposed to be a key contributor to age-associated cellular decline. Transposons are mobile genetic elements capable of inserting into new genomic locations, thus having the potential to increase genomic instability. Consistent with this, transposon expression generally increases with age. However, the extent to which transposon insertions accumulate to disrupt the genome of cells within aging individuals has remained an open question. We specifically answer this through single cell whole genome sequencing and find that transposon insertions do not increase with age. Even though insertions did not increase, the expression of transposons is linked to aging, as reducing the expression of individual transposons extended lifespan. Transcriptome studies of these long-lived flies revealed increased expression of genes linked to proteolysis genes and to functioning of the immune system. Our study therefore establishes transposon expression, and not insertion, as a critical contributor to animal aging.

genetics↗

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↗

Cannabidiol targets a modulatory system for excitatory-inhibitory synaptic coordination, contributing to its anti-seizure action

Cannabidiol (CBD), a non-euphoric component of cannabis, reduces seizures in multiple forms of pediatric epilepsy, but the mechanism(s) of anti-seizure action remain unclear. In one leading model, CBD acts at glutamatergic axon terminals, blocking pro-excitatory actions of an endogenous membrane phospholipid, lysophosphatidylinositol (LPI), at the G protein-coupled receptor GPR55. However, the impact of LPI-GPR55 signaling at inhibitory synapses and in epileptogenesis remains underexplored. We found that LPI transiently increased hippocampal CA3[->]CA1 excitatory presynaptic release probability and evoked synaptic strength in WT mice, while attenuating inhibitory postsynaptic strength by decreasing GABAAR{gamma}2 and gephyrin puncta. Effects of LPI at both excitatory and inhibitory synapses were eliminated by CBD pretreatment and absent after GPR55 deletion. Acute pentylenetrazole-induced seizures elevated levels of GPR55 and LPI, and chronic lithium pilocarpine-induced epileptogenesis potentiated the pro-excitatory effects of LPI. We propose that CBD exerts potential therapeutic effect both by blocking synaptic effects of LPI and dampening hyperexcitability.

neuroscience↗

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

genetics↗

SRSF2 is required for mRNA splicing and spermatogenesis

RNA splicing plays significant roles in fundamental biological activities. However, our knowledge about the roles of alternative splicing and underlying mechanisms during spermatogenesis is limited. Here, we report that Serine/arginine-rich splicing factor 2 (SRSF2), also known as SC35, plays critical roles in alternative splicing and male reproduction. Male germ cell-specific deletion of Srsf2 by Stra8-Cre caused complete infertility and defective spermatogenesis. Further analyses revealed that deletion of Srsf2 disrupted differentiation and meiosis initiation of spermatogonia. Mechanistically, by combining RNA-seq data with LACE-seq data, we showed that SRSF2 regulatory networks play critical roles in several major events including reproductive development, spermatogenesis, meiotic cell cycle, synapse organization, DNA recombination, chromosome segregation, and male sex differentiation. Furthermore, SRSF2 affected expression and alternative splicing of Stra8, Stag3 and Atr encoding critical factors for spermatogenesis in a direct manner. Taken together, our results demonstrate that SRSF2 has important functions in spermatogenesis and male fertility by regulating alternative splicing.

developmental biology↗

Systematic mutagenesis reveals critical effector functions in the assembly and dueling of the H1-T6SS in Pseudomonas aeruginosa

Pseudomonas aeruginosa is an important human pathogen that can cause severe wound and lung infections. It employs the type VI secretion system (H1-T6SS) as a molecular weapon to carry out a unique dueling response to deliver toxic effectors to neighboring sister cells or other microbes after sensing an external attack. However, the underlying mechanism for such dueling is not fully understood. Here, we examined the role of all H1-T6SS effectors and VgrG proteins in assembly and signal sensing by ectopic expression, combinatorial deletion and point mutations, and imaging analyses. Expression of effectors targeting the cell wall and membrane resulted in increased H1-T6SS assembly. Deletion of individual effector and vgrG genes had minor- to-moderate effects on H1-T6SS assembly and dueling activities. The dueling response was detectable in the P. aeruginosa mutant lacking all H1-T6SS effector activities. In addition, double deletions of vgrG1a with either vgrG1b or vgrG1c and double deletions of effector genes tse5 and tse6 severely reduced T6SS assembly and dueling activities, suggesting their critical role in T6SS assembly. Collectively, these data highlight the diverse roles of effectors in not only dictating antibacterial functions but also their differential contributions to the assembly of the complex H1-T6SS apparatus.

microbiology↗

A dueling-competent signal-sensing module guides precise delivery of cargo proteins into target cells by engineered Pseudomonas aeruginosa

To recognize and manipulate a specific microbe of a crowded community is a highly challenging task in synthetic biology. Here, we introduce a highly-selective protein delivery platform, termed DUEC, which responds to direct contact of attacking cells by engineering the tit-for-tat/dueling response of H1-T6SS (type VI secretion system) in Pseudomonas aeruginosa. Using a Cre-recombinase-dependent reporter, we screened H1-T6SS secreted substrates and developed Tse6N as the most effective secretion tag for Cre delivery. DUEC cells can discriminately deliver the Tse6N-Cre cargo into the cytosol of T6SS+ but not T6SS- Vibrio cholerae cells in a mixed population. These data demonstrate that the DUEC cell is not only a prototypical physical-contact sensor and delivery platform but also may be coupled with recombination-based circuits with the potential for complex tasks in mixed microbial communities.

microbiology↗

Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions

Non-coding RNA structure and function are essential to understanding various biological processes, such as cell signaling, gene expression, and post-transcriptional regulations. These are all among the core problems in the RNA field. With the rapid growth of sequencing technology, we have accumulated a massive amount of unannotated RNA sequences. On the other hand, expensive experimental observatory results in only limited numbers of annotated data and 3D structures. Hence, it is still challenging to design computational methods for predicting their structures and functions. The lack of annotated data and systematic study causes inferior performance. To resolve the issue, we propose a novel RNA foundation model (RNA-FM) to take advantage of all the 23 million non-coding RNA sequences through self-supervised learning. Within this approach, we discover that the pre-trained RNA-FM could infer sequential and evolutionary information of non-coding RNAs without using any labels. Furthermore, we demonstrate RNA-FMs effectiveness by applying it to the downstream secondary/3D structure prediction, SARS-CoV-2 genome structure and evolution prediction, protein-RNA binding preference modeling, and gene expression regulation modeling. The comprehensive experiments show that the proposed method improves the RNA structural and functional modelling results significantly and consistently. Despite only being trained with unlabelled data, RNA-FM can serve as the foundational model for the field.

bioinformatics↗