Biology subjects

Ma, X.

Publications and source records attributed to Ma, X..

At least 163 records · Page 9Linked to original sources

bioRxiv2024

Shared and Unique Neural Codes for Biological Motion Perception in Humans and Macaque Monkeys

Throughout evolution, living organisms have honed the ability to swiftly recognize biological motion (BM) across species. However, how the brain processes within- and cross-species BM, and the evolutionary progression of these processes, remain unclear. To investigate these questions, we examined brain activity in the lateral temporal areas of humans and monkeys as they passively observed upright and inverted human and macaque BM stimuli. In humans, the middle temporal area (hMT+) responded to both human and macaque BM stimuli, while the right posterior superior temporal sulcus (pSTS) exhibited selective responses to human BM stimuli. This selectivity was evidenced by an increased feedforward connection from hMT+ to pSTS during the processing of human BM stimuli. In monkeys, the MT region processed BM stimuli from both species, but no subregion in the STS anterior to MT was specific to conspecific BM stimuli. A comparison of these findings suggests that upstream brain regions (i.e., MT) may retain homologous functions across species, while downstream brain regions (i.e., STS) may have undergone differentiation and specialization throughout evolution. These results provide insights into the commonalities and differences in the specialized visual pathway engaged in processing within- and cross-species BMs, as well as their functional divergence during evolution.

neuroscience↗

bioRxiv2024

Dynamics of duplicated gene regulatory networks governing cotton fiber development following polyploidy

Cotton fiber development entails complex genome-wide gene regulatory networks (GRN) that remain mostly unexplored. Here we present integrative analyses of fiber GRNs using public RNA-seq datasets, integrated with multi-omics genomic, transcriptomic, and cistromic data. We detail the fiber co-expression dynamics and regulatory connections, validating findings with external datasets and transcription factor (TF) binding site data. We elucidate previously uncharacterized TFs that regulate genes involved in fiber-related functions and cellulose synthesis, and identify the regulatory role of two homoeologous G2-like transcription factors on fiber length. Analysis of duplicated gene expression and network relationships in allopolyploid cotton, which has two co-resident genomes (A, D), revealed novel aspects of asymmetric subgenomic developmental contributions. Whereas D-based homoeolog pairs drive higher overall gene expression from the D subgenome, TFs from the A subgenome play a preferential regulatory role in the fiber gene regulatory network. Following allopolyploid formation, it appears that the trans-regulatory roles of TFs diversified more rapidly between homoeologs than did the cis-regulatory elements of their target genes. Our approach underscores the utility of network analysis for detection of master regulators and provides fresh perspectives on fiber development and polyploid functional genomics, through the lens of co-expression and GRN dynamics.

bioinformatics↗

bioRxiv2024

Alleviation of salt stress in strawberries by hydrogen-rich water: physiological, transcriptomic and metabolomic responses

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/605184v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1aa6488org.highwire.dtl.DTLVardef@1ae580borg.highwire.dtl.DTLVardef@11656bcorg.highwire.dtl.DTLVardef@1985c7b_HPS_FORMAT_FIGEXP M_FIG C_FIG With the continuous advancement of climate change and human activities, cultivable land is becoming increasingly susceptible to the influence of salt ions. Therefore, it is crucial to mitigate the salt stress on plants through various approaches. In this study, strawberry seedlings were selected as the experimental plants, and a comprehensive transcriptomic and metabolomic analysis was conducted to elucidate the effects of hydrogen-rich water (HRW) on strawberries under salt stress. The results indicated that HRW significantly promoted plant growth, particularly increasing root biomass by 49.50%. Additionally, HRW regulated the levels of soluble sugars, malondialdehyde (MDA), and antioxidant enzymes, enhancing the cellular uptake of potassium ions and the expulsion of sodium ions. The levels of Ca2+ and Mg2+ in organelles increased by 2.06 and 2.45-fold, respectively. Transcriptomic analysis revealed that HRW substantially altered gene expression in strawberry roots; under salt stress, HRW up-regulated beneficial biological processes. Furthermore, genes related to ion absorption and transport, antioxidant enzymes, and cell wall biosynthesis were screened. Meanwhile, key common pathways were identified in differentially expressed metabolites (DEMs) and differentially expressed genes (DEGs) related to phenylpropane biosynthesis, alanine, aspartate, and glutamate metabolism, amino and nucleotide sugar metabolism, and galactose metabolism. A molecular mechanism for mitigating salt stress in strawberry seedlings by HRW was provided by the integrated approaches in this research, reflecting the potential applications of hydrogen gas in agriculture.

physiology↗

bioRxiv2024

Genomics-FM: Universal Foundation Model for Versatile andData-Efficient Functional Genomic Analysis

Artificial intelligence (AI) plays a crucial role in functional genomic analysis, offering great potential for comprehending biological phenomena such as heredity, development, diseases, and evolution. However, the development of AI models needs substantial labeled data, and these models are typically task-specific with limited generalizability to various applications. Here, we develop Genomics-FM, a genomic vocabulary driven foundation model that enables versatile and label-efficient functional genomic analysis. Specifically, Genomics-FM is first pretrained with ensemble genomic vocabulary on vast unlabelled data to learn comprehensive and generalizable representations and then finetuned with specific genomic vocabulary on limited labeled data to selectively activate and adapt the pretraining knowledge for specific tasks. We show that Genomics-FM significantly reduces the dependence on labeled data, and demonstrates the capability to outperform existing models across a comprehensive suite of tasks including genome annotation, epigenomic and expression profile prediction, and variant effect assessment. Remarkably, Genomics-FM even shows impressive zero-shot predictive capabilities across diverse species and tissues and exhibits noticeable adaptability to RNA-related tasks. With feasibility in data scarcity and even cross-domain biological scenarios, Genomics-FM will promote the broad application of AI and empower researchers to tackle previously insurmountable challenges, paving the way for groundbreaking research and discoveries.

bioinformatics↗

bioRxiv2024

Human microbiome-derived peptide affects the development of experimental autoimmune encephalomyelitis via molecular mimicry

BackgroundGut commensal microbiota has been identified as a potential environmental risk factor for multiple sclerosis (MS), and numerous studies have linked the commensal microorganism with the onset of MS. However, little is known about the mechanisms underlying the gut microbiome and host-immune system interaction. MethodsWe employed bioinformatics methodologies to identify human microbial-derived peptides by analyzing their similarity to the MHC II-TCR binding patterns of self-antigens. Subsequently, we conducted a range of in vitro and in vivo assays to assess the encephalitogenic potential of these microbial-derived peptides. FindingsWe analyzed 304,246 human microbiome genomes and 103 metagenomes collected from the MS cohort and identified 731 nonredundant analogs of myelin oligodendrocyte glycoprotein peptide 35-55 (MOG35-55). Of note, half of these analogs could bind to MHC II and interact with TCR through structural modeling of the interaction using fine-tuned AlphaFold. Among the 8 selected peptides, the peptide (P3) shows the ability to activate MOG35-55-specific CD4+ T cells in vitro. Furthermore, P3 shows encephalitogenic capacity and has the potential to induce EAE in some animals. Notably, mice immunized with a combination of P3 and MOG35-55 develop severe EAE. Additionally, dendritic cells could process and present P3 to MOG-specific CD4+ T cells and activate these cells. InterpretationOur data suggests the potential involvement of a MOG35-55-mimic peptide derived from the gut microbiota as a molecular trigger of EAE pathogenesis. Our findings offer direct evidence of how microbes can initiate the development of EAE, suggesting a potential microbiome-based therapeutic target for inhibiting the progression of MS. FundingNational Natural Science Foundation of China (82371350 to GY) Research in contextO_ST_ABSEvidence before this studyC_ST_ABSOn July 31, 2024, we conducted a search on PubMed for articles containing the phrases "gut microbiome and multiple sclerosis" and "gut microbiome and experimental autoimmune encephalomyelitis." This search yielded a total of 630 and 151 articles, respectively, indicating that the relationship between gut microbiota and the development of MS and EAE is well established. In contrast, our search for "gut microbiome and molecular mimicry and experimental autoimmune encephalomyelitis" revealed only two review papers, highlighting a significant gap in the literature regarding the role of molecular mimicry in connecting gut microbiome dynamics to the development of EAE. Added value of this studyIn this study, we employed bioinformatics tools to screen for microbial-derived peptides in the gut that potentially cross-react with autoantigen-specific TCR. Our key findings include: 1) Identification of MOG35-55 mimics within the human gut microbiome by employing a combination of TCR-binding footprint screening and prediction model of peptide-MHC II-TCR complexes; 2) Microbial-derived MOG35-55 mimics can cross-react with MOG35-55-specific CD4+ T cells; 3) Among them, peptide 3 predicted from Akkermansia muciniphila can induce moderate EAE in mice; 4) Dendritic cells could process and present peptide 3 to MOG-specific CD4+ T cells and activate these cells. Implications of all the available evidenceThis study suggests the potential involvement of a MOG35-55-mimic peptide derived from the gut microbiota as a molecular trigger of EAE pathogenesis. These data may provide a potential microbiome-based therapeutic target for inhibiting the progression of MS.

immunology↗

bioRxiv2024

Targeting NOTCH2-JAG1 juxtacrine signaling reverses macrophage-mediated tumor resistance to taxol

Taxanes are widely used in chemotherapy, but primary and acquired resistance limit the clinical efficacy. Studies have shown tumor interaction with macrophages in the tumor microenvironment (TME) plays a significant role in taxane resistance, yet therapeutic strategies that directly deplete or repolarize macrophages are challenging and with considerable risk of side effects. Here we uncovered that tumor-macrophage interaction can be selectively targeted by inhibiting post-mitotic NOTCH2-JAG1 juxtacrine signaling in the TME, which strongly sensitizes paclitaxel response. Using translatome profiling, we found significant NOTCH2 upregulation during paclitaxel-induced prolonged mitosis. NOTCH2 was subsequently activated in the post-mitotic G1 phase by JAG1 expressed on the neighboring macrophages and tumor cells, which promoted tumor cell survival and upregulated cytokines that recruited JAG1-expressing macrophages, thus generating a positive feedback loop that further enhanced the pro-tumor NOTCH2 activity. By targeting this NOTCH2-JAG1 axis using NOTCH2 shRNA or a pan-NOTCH inhibitor, macrophage recruitment and paclitaxel resistance were significantly attenuated in multiple mouse tumor models of ovarian cancer. Clinical samples from paired primary and recurrent ovarian cancer patients also showed significant correlation of higher NOTCH2 expression with worse prognosis. Our results thus point to combining NOTCH2 inhibitor with taxane as an effective therapeutic strategy to selectively disrupt tumor-macrophage interaction in the TME and overcome macrophage-mediated taxane resistance in NOTCH2-positive tumors.

cancer biology↗

bioRxiv2024

MetaGXplore: Integrating Multi-Omics Data with Graph Convolutional Networks for Pan-cancer Patient Metastasis Identification

The spread of cancer cells from the primary tumor to distant anatomical sites, known as tumor metastasis, poses a significant challenge in clinical prognosis, impairing treatment efficacy and reducing patient survival time. Current methods for predicting and diagnosing tumor metastasis rely heavily on extensive examinations and subjective clinical judgments. Accurate and rapid prediction of tumor metastasis likelihood remains an unresolved challenge, crucial for guiding effective clinical interventions and extending patient survival. Additionally, identifying key genes highly associated with metastasis probability is a pressing issue, essential for providing valuable insights into the potential identification of tumor metastasis-specific biomarkers. We developed MetaGXplore, a pioneering Graph Convolutional Neural Network (GCN)-based framework designed to predict metastasis probability by integrating pan-cancer multi-omic datasets with a protein-protein interaction network, while also identifying key genes involved in the metastatic process. Multi-omics datasets offer a comprehensive view of cancer biology, enhancing accuracy in metastasis forecasting through superior deep learning algorithms. Our classification model results were interpreted with GNNExplainer. The efficacy of MetaGXplore was validated via model evaluations, graph structure analysis, and multi-omics data assessment. Enrichment analysis of key genes further explored their biological roles.

bioinformatics↗

bioRxiv2024

MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning

Spatially resolved transcriptomics simultaneously measure the spatial location, histology images, and transcriptional profiles of the same cells or regions in undissociated tissues. Integrative analysis of multi-modal spatially resolved data holds immense potential for understanding the mechanisms of biology. Here we present a flexible multi-modal contrastive learning for the integration of spatially resolved transcriptomics (MuCST), which jointly perform denoising, elimination of heterogeneity, and compatible feature learning. We demonstrate that MuCST robustly and accurately identifies tissue subpopulations from simulated data with various types of perturbations. In cancer-related tissues, MuCST precisely identifies tumor-associated domains, reveals gene biomarkers for tumor regions, and exposes intra-tumoral heterogeneity. We also validate that MuCST is applicable to diverse datasets generated from various platforms, such as STARmap, Visium, and omsFISH for spatial transcriptomics, and hematoxylin and eosin or fluorescence microscopy for images. Overall, MuCST not only facilitates the integration of multi-modal spatially resolved data, but also serves as pre-processing for data restoration (Python software is available at https://github.com/xkmaxidian/MuCST).

bioinformatics↗

bioRxiv2024

Macrophages facilitate interclonal cooperation-induced tumor heterogeneity and malignancy by activating the innate immune signaling

Tumor heterogeneity is a common hallmark of cancer and is considered a major cause of treatment failure and relapse, yet it remains poorly understood how various types of cells communicate within the tumor microenvironment (TME) to regulate tumor progression in vivo. Here we establish a tumor heterogeneity model in Drosophila eye epithelium by mutating the tricellular junction protein M6 in cells surrounding RasV12benign tumors and dissect the in vivo mechanisms underlying interclonal cooperation-induced malignancy by utilizing sophisticated genetic techniques in conjunction with single-cell RNA sequencing (scRNA-seq). Our findings reveal that loss of M6 facilitates the malignant transformation of neighboring RasV12 tumors by activating the Toll signaling, the innate immune response pathway. Notably, inhibiting Toll signaling impedes tumor progression, whereas its activation synergistically promotes RasV12 tumor malignancy by inactivating the Hippo pathway. Mechanistically, RasV12 tumors surrounded by M6 mutant clones lead to increased recruitment of hemocytes, which are the equivalent of macrophages in Drosophila, in a JNK pathway-dependent manner. Consequently, these tumor-associated macrophages secrete the Spatzle (Spz) ligand, which subsequently activates the Toll receptor within the RasV12 tumors, thereby triggering tumorigenesis. In summary, our study elucidates the complex in vivo interactions between genetically distinct oncogenic cells and between tumors and macrophages, shedding light on how macrophages exploit the innate immune signaling within tumors to regulate tumor heterogeneity and promote tumor progression. Significance statementIntratumoral heterogeneity profoundly affects cancer development and treatment in human tumors. The intricate nature of tumor cells and the presence of diverse cell types pose challenges to uncovering in vivo mechanisms responsible for heterogeneity. Our Drosophila tumor heterogeneity model reveals that fruit fly macrophages promotes both tumor heterogeneity and malignancy. Following recruitment by tumor cells, these macrophages secrete the ligand Spz to activate the Toll signaling pathway within tumor cells, which subsequently inactivates the Hippo pathway to drive tumorigenesis. Our study highlights the crucial role of hemocytes as intermediaries in coordinating tumor heterogeneity and facilitating intercellular communication between different cells within the TME.

cancer biology↗

bioRxiv2024

BEACON: Benchmark for Comprehensive RNA Tasks and Language Models

RNA plays a pivotal role in translating genetic instructions into functional outcomes, underscoring its importance in biological processes and disease mechanisms. Despite the emergence of numerous deep learning approaches for RNA, particularly universal RNA language models, there remains a significant lack of standardized benchmarks to assess the effectiveness of these methods. In this study, we introduce the first comprehensive RNA benchmark BEACON (BEnchmArk for COmprehensive RNA Task and Language Models). First, BEACON comprises 13 distinct tasks derived from extensive previous work covering structural analysis, functional studies, and engineering applications, enabling a comprehensive assessment of the performance of methods on various RNA understanding tasks. Second, we examine a range of models, including traditional approaches like CNNs, as well as advanced RNA foundation models based on language models, offering valuable insights into the task-specific performances of these models. Third, we investigate the vital RNA language model components from the tokenizer and positional encoding aspects. Notably, our findings emphasize the superiority of single nucleotide tokenization and the effectiveness of Attention with Linear Biases (ALiBi) over traditional positional encoding methods. Based on these insights, a simple yet strong baseline called BEACON-B is proposed, which can achieve outstanding performance with limited data and computational resources. The datasets and source code of our benchmark are available at https://github.com/terry-r123/RNABenchmark.

bioinformatics↗

bioRxiv2024

Nuclear receptor E75/NR1D2 drives tumor malignant transformation by integrating Hippo and Notch pathways

Hormone therapy resistance and the ensuing aggressive progression of tumors present a significant clinical challenge. However, the mechanisms underlying the induction of tumor malignancy by hormone inhibition remain poorly understood. Here we show that Drosophila malignant epithelial tumors exhibit a comparable decrease in ecdysone signaling, the primary steroid hormone pathway in Drosophila. Furthermore, we find that ectopic expression of the nuclear receptor E75 partially mimics ecdysone signaling inhibition, specifically promoting the malignant transformation of benign tumors by integrating the Hippo and Notch signaling pathways. Genome-wide DNA binding profiles and biochemistry data reveal that E75 not only physically interacts with the transcription factors of both Hippo and Notch pathways, but also exhibits widespread co-binding to their target genes, thus contributing to tumor malignancy. Moreover, we validate these findings by demonstrating that depletion of NR1D2, the mammalian equivalent of E75, inhibits the activation of Hippo and Notch target genes, impeding glioblastoma progression in vivo. In summary, our study unveils a previously unrecognized mechanism by which hormone inhibition promotes tumor malignant transformation, while providing a conserved mechanistic understanding of how Hippo and Notch pathways are integrated by the oncogene E75/NR1D2 during tumor progression.

cancer biology↗

bioRxiv2024

Intra-genomic genes-to-genes correlation enables genome representaion

The bacterial pan-genome consists of core genes shared by all members of a taxonomy and accessory genes found in only a subset. The correlation among genes within the pan-genome could advance our understanding of evolution and tackle medical challenges. Here, we discovered a strong intra-genomic correlation among bacterial pan-genes within each of Escherichia coli, Listeria monocytogenes, Staphylococcus aureus, and Campylobacter jejuni. With a convolutional neural network assisted core genome knock-out simulation, we found that different combinations of fewer than 20 highly variable core genes could recover the sub-species type classified by complete core genome with accuracy >95%. This observation led us to test the genes-to-genes predictability: with more than 52,000 assemblies from each species, combinations of highly variable core genes could predict the sequence variants of other core genes (average accuracy >94%) within the same genome and could also predict sequence variants (average accuracy >91%) as well as the presence (average AUROC >0.91) of some accessory genes. Furthermore, combinations of highly variable core genes could also predict multiple antibiotic resistances (AUROC >0.80) in large published datasets of E. coli, S. aureus, and Mycobacterium tuberculosis. Collectively, we propose that genes within the same genome can strongly correlate with each other. Therefore, the strain phylogeny and the status of other genes could be uniformly represented by combinations of highly variable core genes, which could further represent certain phenotypes including in vitro resistance.

bioinformatics↗

bioRxiv2024

Unveiling the PHR-centered regulatory network orchestrating the phosphate starvation signaling in Chinese fir (Cunninghamia lanceolata)

Phosphorus (P) is an essential mineral element for plant growth and is absorbed and utilized in the form of inorganic phosphate (Pi). However, Pi deficiency largely restricts plant growth in forest ecosystems, while the molecular mechanism of Pi deficiency in woody plants remains unclear. Here, we show that PHOSPHATE STARVATION RESPONSE (PHRs) were central regulators of Pi starvation signaling in Chinese fir, a gymnosperm woody plant. Pi deficiency repressed the shoot growth by decreasing the net photosynthesis rate, reducing the size and number of needle leaves, suppressing the plant height, and reducing the biomass accumulation of shoots in Chinese fir seedlings. Thirteen Chinese fir PHRs (ClPHRs) were characterized, which evolved differently from model and angiosperm woody plants. ClPHRs did not respond to Pi deficiency at the transcriptional level, whereas three ClPHRs responded to Pi deficiency by increasing the nuclear/cytoplasmic protein abundance ratio. Four ClPHRs can restore Pi starvation signaling by activating transcription of AtPHT1;1 and AtPHT1;4 in the atphr1 mutant. Notably, ClPHR7, which is evolutionarily distinct from AtPHR1, was the only ClPHR that could respond to Pi deficiency and restore Pi starvation signals. ClPHR7 could also interact with SPX through protein-protein interaction analysis. Thus, the SPX-PHR regulatory module was also present in gymnosperm woody plants, but the exactly responsible proteins were evolutionarily different from those of model plants. In summary, our results revealed the function of the SPX-PHR regulatory module in Pi starvation signaling and provided genetic information for engineered woody plants with high Pi use efficiency.

plant biology↗

bioRxiv2024

Activation of three targets by a TAL effector confers susceptibility to bacterial blight of cotton

Xanthomonas spp. employ transcription activator-like effectors (TALEs) to promote pathogenicity by activating host susceptibility (S) genes. Cotton GhSWEET10 is an S gene targeted by a TALE in an early isolate of Xanthomonas citri pv. malvacearum (Xcm), but not by recent field Xcm isolates. To understand the pathogenicity shift in Xcm and its adaptation to cotton, we assembled the whole genome and the TALE repertoire of three recent Xcm Texas field isolates. A newly evolved TALE, Tal7b, activated different GhSWEET genes, GhSWEET14a and GhSWEET14b. Simultaneous activation of GhSWEET14a and GhSWEET14b resulted in pronounced water-soaked lesions. Transcriptome profiling coupled with TALE-binding element prediction identified a pectin lyase as an additional Tal7b target, quantitatively contributing to Xcm virulence alongside GhSWEET14a/b. CRISPR-Cas9-based gene editing supported the function of GhSWEETs as S genes in cotton bacterial blight and the promise of disrupting the TALE-binding site in these genes to control the disease. Collectively, our findings elucidate the rapid evolution of TALEs in Xanthomonas field isolates and highlight the virulence mechanism wherein TALEs induce multiple S genes simultaneously to promote pathogenicity.

plant biology↗

bioRxiv2024

mTORC2-mediated cell-cell interaction promote BMP4-induced WNT activation and mesoderm differentiation

The mechanistic target of rapamycin complex 2 (mTORC2) is essential for embryonic development but its underlying molecular mechanisms remain unclear. Here we show that disruption of mTORC2 in human embryonic stem cells (hESCs) considerably alters the Rho/Rac signaling dynamics and reduces cell adhesion. Despite this, mTORC2-deficient hESCs maintain self-renewal and expression of pluripotent markers when cultured in mouse-embryonic fibroblast conditioned medium supplemented with bFGF (MEF-CM). However, these hESCs exhibit significantly impaired mesoderm and endoderm differentiation in response to BMP4 and Activin, respectively, due to reduced WNT activation mediated by cell-cell interactions. Direct activation of the WNT pathway by a GSK3 inhibitor restores mesendoderm differentiation in mTORC2-deficient hESCs. Our study uncovers a novel mechanism by which mTORC2 regulates cell fate determination and highlights a critical link between the intercellular adhesion and the activation of canonical WNT genes.

cell biology↗

bioRxiv2024

Less is more: selection from a small set of options improves BCI velocity control

We designed the discrete direction selection (DDS) decoder for intracortical brain computer interface (iBCI) cursor control and showed that it outperformed currently used decoders in a human-operated real-time iBCI simulator and in monkey iBCI use. Unlike virtually all existing decoders that map between neural activity and continuous velocity commands, DDS uses neural activity to select among a small menu of preset cursor velocities. We compared closed-loop cursor control across four visits by each of 48 naive, able-bodied human subjects using either DDS or one of three common continuous velocity decoders: direct regression with assist (an affine map from neural activity to cursor velocity), ReFIT, and the velocity Kalman Filter. DDS outperformed all three by a substantial margin. Subsequently, a monkey using an iBCI also had substantially better performance with DDS than with the Wiener filter decoder (direct regression decoder that includes time history). Discretizing the decoded velocity with DDS effectively traded high resolution velocity commands for less tortuous and lower noise trajectories, highlighting the potential benefits of simplifying online iBCI control.

neuroscience↗

bioRxiv2024

SLO2.1/NALCN Functional Complex Activity in Mouse Myometrial Smooth Muscle Cells During Pregnancy.

At the end of pregnancy, the uterus transitions from a quiescent to a highly contractile state. This is partly due to depolarization of the resting membrane potential in uterine (myometrial) smooth muscle cells (MSMCs). In human MSMCs, the membrane potential is regulated by a functional complex between the sodium (Na+)-activated potassium (K+) channel SLO2.1 and the Na+ Leak Channel Non-Selective (NALCN). Na+ entering through NALCN activates SLO2.1, leading to K+ efflux, membrane hyperpolarization (cells become more negative inside), and reduced contractility. Decreased SLO2.1/NALCN activity results in reduced K+ efflux, leading to membrane depolarization, Ca2+ influx via voltage-dependent calcium channels, and increased MSMC contractility. However, all of these data are from MSMCs isolated from women at term, so the role of the SLO2.1/NALCN complex early in pregnancy was speculative. To address this question here, we examined the role of the SLO2.1/NALCN complex in regulating mouse MSMC membrane potential across pregnancy. We report that Slo2.1 and Nalcn are more highly expressed in MSMCs from non-pregnant and early pregnant mice than in those from late-pregnant mice. Functional studies revealed that SLO2.1 channels mediate a significant portion of the K+ current in mouse MSMCs, particularly in cells from non-pregnant and early pregnant mice. Activation of SLO2.1 by Na+ influx through NALCN led to membrane hyperpolarization in MSMCs from early pregnancy but not in MSMCs from later pregnancy. Moreover, the NALCN/SLO2.1 complex regulates intracellular Ca2+ responses more in MSMCs from non-pregnant and early pregnancy mice than in MSMCs from late pregnancy. Together, these findings reveal that the SLO2.1/NALCN functional complex is conserved between mouse and humans and functions throughout pregnancy. This work could open avenues for targeted pharmacological interventions for pregnancy-related complications.

physiology↗

bioRxiv2024

Establishing remote communication between human operator and engineered intestinal microbe via bio-electronic optical language

Synthetic biology enables microbes to be engineered to detect biomarkers and deliver therapies in situ, offering advantages such as self-replication and localized response and treatment. However, the engineered microbes in the intestine remains a "black box", the status of microbial functionality is inaccessible, and the activation of microbial functions is uncontrollable. There is a demand of a "language" between microbes and human for real-time and in-situ monitoring and controlling engineered microbes in the intestine. Light, due to its advantages of specificity and accuracy in the body, was chosen as the language to establish an interactive communication path between human and the microbes with the features of sophisticated monitoring and controlling. For effectively remote operation of this "language" in the intestine, we introduced an electronic capsule as the intermedia, translating information and instructions understandable for human operator into bacterial regulatory and detectable signals in vivo. In this paper, the electronic capsule and the engineered Escherichia coli Nissle 1917 (EcN) strains were designed in a collaborative manner. An EcN-to-capsule bioluminescent signal transmission was established and testified as the language to report the status of engineered EcN, especially the response of EcN to intestinal environment. Similarly, another capsule-to-EcN optogenetic signal transmission was established and testified as the language to control the function of engineered EcN, especially the secretion of therapeutic substances. On this basis, bidirectional communication between human operator and intestinal microbes was achieved via bidirectional bio-electronic optical language. The communication was established to monitor and regulate engineered EcN community in the intestine in 50-90 kg live pigs. The in vitro and in vivo estimations demonstrated the capabilities of monitoring and regulating the engineered microbes, offering a remotely controllable language-based communication between human operator and internal intestinal microbes.

synthetic biology↗