Biology subjects

Zhang, B.

Publications and source records attributed to Zhang, B..

At least 379 records · Page 21Linked to original sources

bioRxiv2023

A burns and COVID-19 shared stress responding gene network deciphers CD1C-CD141- DCs as the key cellular components in septic prognosis

Differential body responses to various stresses, infectious or noninfectious, govern clinical outcomes ranging from asymptoma to death. However, the common molecular and cellular nature of the stress responsome across different stimuli is not described. In this study, we compared the expression behaviors between burns and COVID-19 infection by choosing the transcriptome of peripheral blood from related patients as the analytic target since the blood cells reflect the systemic landscape of immune homeostasis. We identified an immune co-stimulator (CD86)-centered network, named stress-response core (SRC), which coordinated multiple immune processes and was robust in membership and highly related to the clinical traits in both burns and COVID-19. An independent whole blood single-cell RNA sequencing of COVID-19 patients demonstrated that the monocyte-dendritic cell (Mono-DC) wing was the major cellular source of the SRC, among which the higher expression of the SRC in the monocyte was associated with the asymptomatic COVID-19 patients, while the quantity-restricted and function-defected CD1C-CD141-DCs were recognized as the key signature which linked to bad consequences in COVID-19. Specifically, the proportion of the CD1C-CD141-DCs and their SRC expression levels were step-wise reduced along with worse clinic conditions while the sub-cluster of CD1C-CD141-DCs of the critical COVID-19 patients was characterized of IFN signaling quiescence, high mitochondrial metabolism and immune-communication inactivation. Thus, our study identified an expression-synchronized and function-focused gene network which was decreased under burns and COVID-19 stress and argued the CD1C-CD141-DC as the prognosis-related cell population which might serve as a new target of diagnosis and therapy.

immunology↗

bioRxiv2023

Streamline unsupervised machine learning to survey and graph indel-based haplotypes from pan-genomes

Identification and visualization of large insertion and deletion (indel) polymorphisms, which contribute significantly to natural phenotypic variation, are challenge from a pan-genome. Here, through streamlining two unsupervised machine learning algorithms, we developed a BRIDGEcereal webapp for surveying and graphing indel-based haplotypes for genes of interest from publicly accessible pangenomes. Over hundreds of assemblies from five major cereals were compiled. We demonstrated the potential of BRIDGEcereal in exploring natural variation with wheat candidate genes within QTLs and GWAS intervals. BRIDGEcereal is available from https://bridgecereal.scinet.usda.gov.

bioinformatics↗

bioRxiv2023

MGA deletion leads to Richter's transformation via modulation of mitochondrial OXPHOS

Richters transformation (RT) is a progression of chronic lymphocytic leukemia (CLL) to aggressive lymphoma. MGA (Max gene associated), a functional MYC suppressor, is mutated at 3% in CLL and 36% in RT. However, genetic models and molecular mechanisms of MGA deletion driving CLL to RT remain elusive. We established a novel RT mouse model by knockout of Mga in the Sf3b1/Mdr CLL model via CRISPR-Cas9 to determine the role of Mga in RT. Murine RT cells exhibit mitochondrial aberrations with elevated oxidative phosphorylation (OXPHOS). We identified Nme1 (Nucleoside diphosphate kinase) as a Mga target through RNA sequencing and functional characterization, which drives RT by modulating OXPHOS. As NME1 is also a known MYC target without targetable compounds, we found that concurrent inhibition of MYC and ETC complex II significantly prolongs the survival of RT mice in vivo. Our results suggest that Mga-Nme1 axis drives murine CLL-to-RT transition via modulating OXPHOS, highlighting a novel therapeutic avenue for RT. Statement of SignificanceWe established a murine RT model through knockout of Mga in an existing CLL model based on co-expression of Sf3b1-K700E and del(13q). We determined that the MGA/NME1 regulatory axis is essential to the CLL-to-RT transition via modulation of mitochondrial OXPHOS, highlighting this pathway as a novel target for RT treatment.

cancer biology↗

bioRxiv2023

High-Quality Nuclei Isolation from Postmortem Human Heart Muscle Tissues for Single-Cell Studies

Single-cell approaches have become an increasingly popular way of understanding the genetic factors behind disease. Isolation of DNA and RNA from human tissues is necessary to analyze multi-omic data sets, providing information on the single-cell genome, transcriptome, and epigenome. Here, we isolated high-quality single-nuclei from postmortem human heart tissues for DNA and RNA analysis. Postmortem human tissues were obtained from 106 individuals, 33 with a history of myocardial disease, diabetes, or smoking, and 73 controls without heart disease. We demonstrated that the Qiagen EZ1 instrument and kit consistently isolated genomic DNA of high yield, which can be used for checking DNA quality before conducting single-cell experiments. Here, we provide a method for single-nuclei isolation from cardiac tissue, otherwise known as the SoNIC method, which allows for the isolation of single cardiomyocyte nuclei from postmortem tissue by nuclear ploidy status. We also provide a detailed quality control measure for single-nuclei whole genome amplification and a pre-amplification method for confirming genomic integrity.

genetics↗

bioRxiv2023

KDM2B regulates hippocampal morphogenesis by transcriptionally silencing Wnt signaling in neural progenitors

The hippocampus plays major roles in learning and memory. Similar to other parts of the brain, the development of hippocampus requires precise coordination of patterning, cell proliferation, differentiation, and migration, with both cell-intrinsic and extrinsic mechanisms involved. Here we genetically removed the chromatin-association capability of KDM2B - a key component of the variant Polycomb repressive complex 1 (PRC1) - in the progenitors of developing dorsal telencephalon (Kdm2b{Delta}CxxC) to surprisingly discover that the size of Kdm2b{Delta}CxxC hippocampus, particularly the dentate gyrus, became drastically smaller with disorganized cellular components and structure. Kdm2b{Delta}CxxC mice displayed prominent defects in spatial memory, motor learning and fear conditioning. The differentiation trajectory of the developing Kdm2b{Delta}CxxC hippocampus was greatly delayed, with a significant amount of TBR2-expressing intermediate progenitors stuck along the migratory/differentiation path. Transcriptome and chromatin immunoprecipitation studies of neonatal hippocampi and their progenitors indicated that genes implicated in stemness maintenance, especially components of canonical Wnt signaling, could not be properly silenced by PRC1 and PRC2. Activating the Wnt signaling disturbed hippocampal neurogenesis, recapitulating the effect of KDM2B loss. Together, we unveiled a previously unappreciated gene repressive program mediated by KDM2B that controls progressive fate specifications and cell migration, hence morphogenesis of hippocampus during development. Graphic AbstractLoss of KDM2B-CxxC reduces repressive histone modifications - H2AK119ub and H3K27me3 - on key Wnt signal genes, hence leading to the block of their attenuation over time. Hampered differentiation and migration of hippocampal progenitors leads to hippocampal agenesis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/525636v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@18fbbdborg.highwire.dtl.DTLVardef@17633f9org.highwire.dtl.DTLVardef@14e36b9org.highwire.dtl.DTLVardef@1eadb8a_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2023

Multimodal characterization of antigen-specific CD8+ T cells across SARS-CoV-2 vaccination and infection.

The human immune response to SARS-CoV-2 antigen after infection or vaccination is defined by the durable production of antibodies and T cells. Population-based monitoring typically focuses on antibody titer, but there is a need for improved characterization and quantification of T cell responses. Here, we utilize multimodal sequencing technologies to perform a longitudinal analysis of circulating human leukocytes collected before and after BNT162b2 immunization. Our data reveal distinct subpopulations of CD8+ T cells which reliably appear 28 days after prime vaccination (7 days post boost). Using a suite of cross-modality integration tools, we define their transcriptome, accessible chromatin landscape, and immunophenotype, and identify unique biomarkers within each modality. By leveraging DNA-oligo-tagged peptide-MHC multimers and T cell receptor sequencing, we demonstrate that this vaccine-induced population is SARS-CoV-2 antigen-specific and capable of rapid clonal expansion. Moreover, we also identify these CD8+ populations in scRNA-seq datasets from COVID-19 patients and find that their relative frequency and differentiation outcomes are predictive of subsequent clinical outcomes. Our work contributes to our understanding of T cell immunity, and highlights the potential for integrative and multimodal analysis to characterize rare cell populations.

genomics↗

bioRxiv2023

Deep learning prediction boosts phosphoproteomics-based discoveries through improved phosphopeptide identification

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples, but low phosphopeptide identification rate in data analysis limits the potential of this technology. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19%-46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

bioinformatics↗

bioRxiv2022

A method for differential expression analysis and pseudo- temporal locating and ordering of genes in single-cell transcriptomic data

Identification of differentially expressed genes (DEGs) is a pivotal step in single-cell RNA sequencing (scRNA-seq) data analysis. The sparsity and multi-model distribution of scRNA-seq data decides that the traditional tools designed for bulk RNA-seq have several limitations when applied to single-cell data. On the other hand, tools specifically for DEGs analysis of scRNA-seq data normally does not consider the high dimensionality of the data. To this end, we present DEAPLOG, a method for differential expression analysis and pseudo-temporal locating and ordering of genes in single-cell transcriptomic data. We show that DEAPLOG has higher accurate and efficient in DEGs identification when compared with existing methods in both artificial and real datasets. Additionally, DEAPLOG can infer pseudo-time and embedding coordinates of genes, therefore is useful in identifying regulators in trajectory of cell fate decision.

bioinformatics↗

bioRxiv2022

Effects of nonantibiotic alternative growth promoter combinations on nutrient utilization, digestive enzyme activity, intestinal morphology, and cecal microflora of broilers

Given the ban on antibiotic growth promoters, six nonantibiotic alternative growth promoter combinations (NAGPCs) for broilers were evaluated. All birds were fed pellets of two basal diets--starter (0-21 d) and grower (22-42 d)--with either enramycin (ENR) or NAGPC supplemented. 1) control + 100 mg/kg ENR; 2) control diet (CON, basal diet); 3) control + 2,000 mg/kg mannose oligosaccharide (MOS) + 300 mg/kg mannanase (MAN) + 1,500 mg/kg sodium butyrate (SB) (MMS); 4) control + 2,000 mg/kg MOS + 300 mg/kg MAN + 500 mg/kg Bacillus subtilis (BS) (MMB); 5) control + 2,000 mg/kg MOS + 9,000 mg/kg fruit oligosaccharide (FOS) + 1,500 mg/kg SB (MFS); 6) control + 9,000 mg/kg FOS + 500 mg/kg BS (MFS) (MBP). The experiment used a completely random block design with six replicates per group: 50 Ross 308 broilers in the starter phase and 16 in the grower phase. All the NAGPCs significantly improved (P < 0.01) utilization of dry matter (DM), organic matter (OM), crude protein (CP), and crude fat (CF) on d 21, significantly increased DM, OM (P < 0.01), and CP (P < 0.05) on d 42, and significantly increased (P < 0.01) villus height, crypt depth, and the villus height to crypt depth ratio in the jejunum and ileum compared with CON and ENR. On d 21 and 42, trypsin, lipase, and amylase activity of the duodenum significantly increased in the MMS, MMB, MFB, and MFM groups. Compared with ENR and CON, MMS, MMB, and MBP increased the abundance of Firmicutes at d 21 and of Bacteroides at d 42 whereas MMB, MFB, and MBP decreased the abundance of Proteobacteria at d 21 and 42. Overall, the NAGPCs were found to have some beneficial effects and may be used as effective antibiotic replacements in broilers.

biophysics↗

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

A unified classification system for HIV-1 5' long terminal repeats

The HIV-1 provirus mainly consists of internal coding region flanked by the 2 same long terminal repeats (LTRs) at each terminus. The LTRs play important roles in HIV-1 reverse transcription, integration, and transcription by the association with host factors. However, despite of the significant study advances of the internal coding regions of HIV-1 by using definite reference classification, there are no systematic classifications for HIV-1 5 LTRs, which hinders our elaboration on 5 LTR and a better understanding of the viral origin, spread and therapy. Here, by analyzing all available resources of 5 LTR sequences in public databases following 4 recognized principles for the reference classification, 83 representatives and 14 consensus sequences were identified as representatives of 2 groups, 6 subtypes, 6 sub-subtypes, and 9 CRFs. To test the reliability of our established classification system, the constructed references were applied to identify the 5 LTR assignment of the 22 clinical isolates in China. The results revealed that 16 out of 22 tested strains showed a consistent subtype classification with the previous LTR-independent classification system. However, 6 strains, for which recombination events within 5 LTR were demonstrated, unexpectedly showed a different subtype classification, leading a significant change of binding sites for important transcription factors including SP1, p53, and NF-{kappa}B. The binding change of these transcriptional factors would probably affect the transcriptional activity of 5 LTR. This study established a unified classification system for HIV-1 5 LTRs, which will facilitate HIV-1 characterization and be helpful for both basic and clinical research fields. IMPORTANCEHere, a scientific, reliable, and usable classification system based on the 5 LTR sequences was established, which will allow us to effectively facilitate the precise typing of HIV-1 strains. This classification system was applied to 22 HIV-1 strains circulating in China, we found that 6 out of 22 strains analyzed, belonged to a different subtype when our results were compared to those obtained with the previous LTR-independent classification system. Thus, these data demonstrated that our classification method could greatly improve the HIV-1 subtype classification. We found that 6 5 LTR sequences showed recombination events, leading to a significant exchange of the binding sites of transcriptional factors. Thus, this work established a comprehensive HIV-1 5 LTR classification system, which will help the scientific community to precisely characterize HIV-1 variants, and better understand the origin and spread of HIV-1 strains, and it also may be helpful for pathogenicity and transmissibility evaluation studies.

microbiology↗

bioRxiv2022

Histone monoaminylation dynamics are regulated by a single enzyme and promote neural rhythmicity

Histone H3 monoaminylations at glutamine(Q) 5 represent an important family of epigenetic markers in neurons that play critical roles in the mediation of permissive gene expression (1, 2). We previously demonstrated that H3Q5 serotonylation(ser) and dopaminylation(dop) are catalyzed by the Transglutaminase 2 (TGM2) enzyme and alter both local and global chromatin states (3, 4). Here, we found that TGM2 additionally functions as an "eraser" of H3 monoaminylations that is capable of "re-writing" these epigenetic marks in cells, including a new class of this modification, H3Q5 histaminylation(his), which displays dynamic diurnal expression in brain and contributes to neural rhythmicity. We found that H3Q5his inhibits binding of the MLL1 complex to the H3 N-terminus and attenuates its methyltransferase activity on H3 lysine(K) 4. We determined that H3Q5 monoaminylation dynamics are dictated by local monoamine concentrations, which are utilized by TGM2. Taken together, we present here a novel mechanism through which a single chromatin regulatory enzyme is capable of sensing chemical microenvironments to affect the epigenetic states of cells. One sentence summaryA single enzyme, TGM2, bidirectionally controls H3 monoaminylation dynamics, which, in turn, facilitate neural rhythmicity.

molecular biology↗

bioRxiv2022

Gut microbiota dysbiosis is associated with altered tryptophan metabolism and dysregulated inflammatory response in severe COVID-19

The clinical course of the 2019 coronavirus disease (COVID-19) is variable and to a substantial degree still unpredictable, especially in persons who have neither been vaccinated nor recovered from previous infection. We hypothesized that disease progression and inflammatory responses were associated with alterations in the microbiome and metabolome. To test this, we integrated metagenome, metabolome, cytokine, and transcriptome profiles of longitudinally collected samples from hospitalized COVID-19 patients at the beginning of the pandemic (before vaccines or variants of concern) and non-infected controls, and leveraged detailed clinical information and post-hoc confounder analysis to identify robust within- and cross-omics associations. Severe COVID-19 was directly associated with a depletion of potentially beneficial intestinal microbes mainly belonging to Clostridiales, whereas oropharyngeal microbiota disturbance appeared to be mainly driven by antibiotic use. COVID-19 severity was also associated with enhanced plasma concentrations of kynurenine, and reduced levels of various other tryptophan metabolites, lysophosphatidylcholines, and secondary bile acids. Decreased abundance of Clostridiales potentially mediated the observed reduction in 5-hydroxytryptophan levels. Moreover, altered plasma levels of various tryptophan metabolites and lower abundances of Clostridiales explained significant increases in the production of IL-6, IFN{gamma} and/or TNF. Collectively, our study identifies correlated microbiome and metabolome alterations as a potential contributor to inflammatory dysregulation in severe COVID-19. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=150 HEIGHT=200 SRC="FIGDIR/small/518860v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@afc4edorg.highwire.dtl.DTLVardef@1a9ac2aorg.highwire.dtl.DTLVardef@65fb46org.highwire.dtl.DTLVardef@153ee6a_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2022

Cleavage of the pseudoprotease iRhom2 by the signal peptidase complex reveals an ER-to-nucleus signalling pathway

iRhoms are pseudoprotease members of the rhomboid-like superfamily and are cardinal regulators of inflammatory and growth factor signalling; they function primarily by recognising transmembrane domains of their clients. Here we report an unexpected, and mechanistically distinct, nuclear function of iRhoms. iRhom2 is a non-canonical substrate of the signal peptidase complex (SPC), the protease that removes signal peptides from secreted proteins. Cleavage of iRhom2 generates an N-terminal fragment that enters the nucleus and modifies the cellular transcriptome. We observed elevated nuclear iRhom2 in skin biopsies of patients with psoriasis and tylosis with oesophageal cancer (TOC); increased SPC-mediated iRhom2 cleavage in a psoriasis model; and overlapping transcriptional signatures between psoriasis and expression of the iRhom2 N-terminus. This work highlights the pathophysiological significance of this SPC-dependent ER-to-nucleus signalling pathway, and is the first example of a rhomboid-like protein that mediates protease-regulated nuclear signalling.

cell biology↗

bioRxiv2022

The RNA binding proteins hnRNP H and F regulate splicing of a MYC dependent HRAS exon in Prostate Cancer Cells

The Myc proto-oncogene contributes to the pathogenesis of more than half of human cancers. Malignant transformation by Myc transcriptionally upregulates the core pre-mRNA splicing machinery and causes mis-regulation of alternative splicing. However, our understanding of how splicing changes are directed by Myc is limited. We performed a signaling pathway-guided splicing analysis to identify Myc dependent splicing events. These included an HRAS cassette exon repressed by Myc across multiple tumor types. To molecularly dissect the regulation of this HRAS exon, we used antisense oligonucleotide tiling to identify splicing enhancers and silencers in its flanking introns. RNA binding motif prediction indicated multiple binding sites for hnRNP H and hnRNP F within these cis-regulatory elements. Using siRNA knockdown and cDNA expression, we found that both hnRNP H and F activate the HRAS cassette exon. Mutagenesis and targeted RNA immunoprecipitation implicate two downstream G-rich elements in this splicing activation. Analyses of ENCODE RNA-seq datasets confirmed hnRNP H regulation of HRAS splicing. Analyses of RNA-seq datasets across multiple cancers showed a negative correlation of hnRNP H gene expression with Myc hallmark enrichment, consistent with the effect of hnRNP H on HRAS splicing. Interestingly, hnRNP F expression showed a positive correlation with Myc hallmarks and thus was not consistent with the observed effects of hnRNP F. Loss of hnRNP H/F altered cell cycle progression and induced apoptosis in the PC3 prostate cancer cell line. Collectively, our results reveal new mechanisms for Myc-dependent regulation of splicing, and point to new possible therapeutic targets in prostate cancers. SIGNIFICANCE STATMENTMyc Transformation by the proto-oncogene c-Myc causes dysregulation of the pre-mRNA splicing reaction in cancer, but it is not known how mRNA isoform changes are directed by Myc. Here, we use bioinformatics to identify a splicing event in another proto-oncogene, HRAS, that is regulated by Myc across multiple tumor types. We identify new splicing regulators, hnRNPs H and F, that control this HRAS exon by binding to enhancer elements within its downstream intron. Additional pan-cancer bioinformatic analyses show hnRNP H expression to be anti- correlated with Myc hallmarks, consistent with the reduced splicing of the HRAS exon in Myc driven cancer. These findings uncover new mechanisms by which Myc can alter splicing in cancer cells and provide new molecular targets for potential therapeutics.

molecular biology↗

bioRxiv2022

OpenFold: Retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization

AlphaFold2 revolutionized structural biology with the ability to predict protein structures with exceptionally high accuracy. Its implementation, however, lacks the code and data required to train new models. These are necessary to (i) tackle new tasks, like protein-ligand complex structure prediction, (ii) investigate the process by which the model learns, which remains poorly understood, and (iii) assess the models generalization capacity to unseen regions of fold space. Here we report OpenFold, a fast, memory-efficient, and trainable implementation of AlphaFold2. We train OpenFold from scratch, fully matching the accuracy of AlphaFold2. Having established parity, we assess OpenFolds capacity to generalize across fold space by retraining it using carefully designed datasets. We find that OpenFold is remarkably robust at generalizing despite extreme reductions in training set size and diversity, including near-complete elisions of classes of secondary structure elements. By analyzing intermediate structures produced by OpenFold during training, we also gain surprising insights into the manner in which the model learns to fold proteins, discovering that spatial dimensions are learned sequentially. Taken together, our studies demonstrate the power and utility of OpenFold, which we believe will prove to be a crucial new resource for the protein modeling community.

bioinformatics↗

bioRxiv2022

Instantaneous antidepressant effect of lateral habenula deep brain stimulation in rats studied with functional magnetic resonance imaging

The available treatments for depression have substantial limitations, including low response rates and substantial lag time before a response is achieved. We applied deep brain stimulation (DBS) to the lateral habenula (LHb) of two rat models of depression (Wistar Kyoto rats and lipopolysaccharide-treated rats) and observed an immediate (within seconds to minutes) alleviation of depressive-like symptoms with a high response rate. Simultaneous functional magnetic resonance imaging (fMRI) conducted on the same sets of depressive rats used in behavioral tests revealed DBS-induced activation of multiple regions in afferent and efferent circuitry of the LHb. The activation levels of brain regions connected to the medial LHb (M-LHb) was correlated with the extent of behavioral improvements. Rats with more medial stimulation sites in the LHb exhibited greater antidepressant effects than those with more lateral stimulation sites. These results indicated that the antidromic activation of the limbic system and orthodromic activation of the monoaminergic systems connected to the M-LHb played a critical role in the rapid antidepressant effects of LHb-DBS. This study indicates that M-LHb-DBS might act as a valuable, rapid-acting antidepressant therapeutic strategy for treatment-resistant depression and demonstrates the potential of using fMRI activation of specific brain regions as biomarkers to predict and evaluate antidepressant efficacy.

neuroscience↗

bioRxiv2022

TimiGP: inferring inter-cell functional interactions and clinical values in the tumor immune microenvironment through gene pairs

Determining how immune cells functionally interact in the tumor microenvironment and identifying their biological roles and clinical values are critical for understanding cancer progression and developing new therapeutic strategies. Here we introduce TimiGP, a computational method to infer inter-cell functional interaction networks and annotate the corresponding prognostic effect from bulk gene expression and survival statistics data. When applied to metastatic melanoma, TimiGP overcomes the prognostic bias caused by immune co-infiltration and identifies the prognostic value of immune cells consistent with their anti- or pro-tumor roles. It reveals the functional interaction network in which the interaction X[->]Y indicates a more positive impact of cell X than Y on survival. This network provides immunological insights to facilitate the development of prognostic models, as evidenced by our computational-friendly, biologically interpretable, independently validated models. By leveraging single-cell RNA-seq data for specific immune cell subsets, TimiGP has the flexibility to delineate the tumor microenvironment at different resolutions and is readily applicable to a wide range of cancer types.

bioinformatics↗