Scientific belief in reconstructing healthy ecology with the power of microorganisms

Distinguishing between swarming and swimming, the two principal forms of bacterial movement, holds significant conceptual and clinical relevance. This is because bacteria that exhibit swarming capabilities often possess unique properties crucial to the pathogenesis of infectious diseases and may also have therapeutic potential. Here, we report a deep learning-based swarming classifier that rapidly and autonomously predicts swarming probability using a single blurry image. Compared with traditional video-based, manually-processed approaches, our method is particularly suited for high-throughput environments and provides objective, quantitative assessments of swarming probability. The swarming classifier demonstrated in our work was trained on Enterobacter sp.

Understanding the specific movements of bacteria isolated from human feces can serve as a novel diagnostic and therapeutic tool for inflammatory bowel disease. Here, we present a protocol for a microbial swarming assay and to isolate the bacteria responsible for swarming activity. We describe steps for identifying bacteria using MALDI-TOF mass spectrometry and whole-genome sequencing. We then detail procedures for validating findings by observing the same swarming phenotype upon reperforming the swarming assay.

Powered by flagella, many bacterial species exhibit collective motion on a solid surface commonly known as swarming. As a natural example of active matter, swarming is also an essential biological phenotype associated with virulence, chemotaxis, and host pathogenesis. Physical changes like cell elongation and hyper-flagellation have been shown to accompany the swarming phenotype.

Bacterial swarming, a collective movement on a surface, has rarely been associated with human pathophysiology. This study aims to define a role for bacterial swarmers in amelioration of intestinal stress.

Bacterial motility under confinement is relevant to both environmental control and the spread of infection. Here, we report observations on Escherichia coli, Enterobacter sp., Pseudomonas aeruginosa, and Bacillus subtilis when they are confined within a thin layer of water around dispersed micrometer-sized particles sprinkled over a semisolid agar gel. In this setting, E. coli and Enterobacteria orbit around the dispersed particles. The liquid layer is shaped like a shallow tent with its height at the center set by the seeding particle, and the meniscus profile set by the strong surface tension of water.

Accurate and robust drug response prediction is of utmost importance in precision medicine. Although many models have been developed to utilize the representations of drugs and cancer cell lines for predicting cancer drug responses (CDR), their performances can be improved by addressing issues such as insufficient data modality, suboptimal fusion algorithms, and poor generalizability for novel drugs or cell lines.

Rare diseases (RDs) may affect individuals in small numbers, but they have a significant impact on a global scale. Accurate diagnosis of RDs is challenging, and there is a severe lack of drugs available for treatment. Pharmaceutical companies have shown a preference for drug repurposing from existing drugs developed for other diseases due to the high investment, high risk, and long cycle involved in RD drug development.

Screening new drug–target interactions (DTIs) by traditional experimental methods is costly and time-consuming. Recent advances in knowledge graphs, chemical linear notations, and genomic data enable researchers to develop computational-based-DTI models, which play a pivotal role in drug repurposing and discovery. However, there still needs to develop a multimodal fusion DTI model that integrates available heterogeneous data into a unified framework.

Knowledge Graph (KG) is becoming increasingly important in the biomedical field. Deriving new and reliable knowledge from existing knowledge by KG embedding technology is a cutting-edge method. Some add a variety of additional information to aid reasoning, namely multimodal reasoning. However, few works based on the existing biomedical KGs are focused on specific diseases.

Circular RNA (circRNA) is a distinguishable circular formed long non-coding RNA (lncRNA), which has specific roles in transcriptional regulation, multiple biological processes. The identification of circRNA from other lncRNA is necessary for relevant research. In this study, we designed attention-based multi-instance learning (MIL) network architecture fed with a raw sequence, to learn the sparse features of RNA sequences and to accomplish the circRNAs identification task. The model outperformed the state-of-art models. Moreover, following the validation of the attention mechanism effectiveness by the handwritten digit dataset, the key sequence loci underlying circRNA’s recognition were obtained based on the corresponding attention score.

Although advances in spatial transcriptomics (ST) enlarge to unveil spatial landscape of tissues, it remains challenging to delineate pathology-relevant and cellular localizations, and interactions exclusive to a spatial niche (e.g., tumor boundary). Here, we develop Cottrazm, integrating ST with hematoxylin and eosin histological image, and single-cell transcriptomics to delineate the tumor boundary connecting malignant and non-malignant cell spots in tumor tissues, deconvolute cell-type composition at spatial location, and reconstruct cell type-specific gene expression profiles at sub-spot level.

Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, the virus has continued to evolve resulting in new waves of infection and immune escape in the vaccinated population.1 The Omicron strains belong to newly prevailing variants of concern (VOCs). They acquired as many as 30 mutations in the spike (S) gene and half of which occur at the receptor-binding domain (RBD) of the S protein.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19.

mTOR serves as a central regulator of cell growth and metabolism by forming two distinct complexes, mTORC1 and mTORC2. Although mechanisms of mTORC1 activation by growth factors and amino acids have been extensively studied, the upstream regulatory mechanisms leading to mTORC2 activation remain largely elusive. Here, we report that the pleckstrin homology (PH) domain of SIN1, an essential and unique component of mTORC2, interacts with the mTOR kinase domain to suppress mTOR activity. More importantly, PtdIns(3,4,5)P3, but not other PtdInsPn species, interacts with SIN1-PH to release its inhibition on the mTOR kinase domain, thereby triggering mTORC2 activation. Mutating critical SIN1 residues that mediate PtdIns(3,4,5)P3 interaction inactivates mTORC2, whereas mTORC2 activity is pathologically increased by patient-derived mutations in the SIN1-PH domain, promoting cell growth and tumor formation. Together, our study unravels a PI3K-dependent mechanism for mTORC2 activation, allowing mTORC2 to activate AKT in a manner that is regulated temporally and spatially by PtdIns(3,4,5)P3.

Plasmacytoid dendritic cells (pDCs) sense viral and microbial DNA through endosomal Toll-like receptors to produce type 1 interferons. pDCs do not normally respond to self-DNA, but this restriction seems to break down in human autoimmune disease by an as yet poorly understood mechanism. Here we identify the antimicrobial peptide LL37 (also known as CAMP) as the key factor that mediates pDC activation in psoriasis, a common autoimmune disease of the skin. LL37 converts inert self-DNA into a potent trigger of interferon production by binding the DNA to form aggregated and condensed structures that are delivered to and retained within early endocytic compartments in pDCs to trigger Toll-like receptor 9. Thus, our data uncover a fundamental role of an endogenous antimicrobial peptide in breaking innate tolerance to self-DNA and suggest that this pathway may drive autoimmunity in psoriasis.

The human genome, comprising approximately 20,000 protein-encoding genes, appears surprisingly modest in complexity when juxtaposed with the genomic repertoire of maize, which boasts around 40,000 such genes (Ezkurdia et al. 2014; Jiao et al. 2017). While this comparison highlights the seemingly limited gene count in humans, it is crucial to recognize that a significant portion of our biological functionality extends beyond our own genome. This is where the concept of the'second genome'comes into play—the microbiome.

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment.

Lipids can be of endogenous or exogenous origin and affect diverse biological functions, including cell membrane maintenance, energy management and cellular signalling. Here, we report >800 lipid species, many of which are associated with health-to-disease transitions in diabetes, ageing and inflammation, as well as cytokine–lipidome networks. We performed comprehensive longitudinal lipidomic profiling and analysed >1,500 plasma samples from 112 participants followed for up to 9 years (average 3.2 years) to define the distinct physiological roles of complex lipid subclasses,

Over the past few decades, most attention to Chinese Cordyceps-associated endogenous microorganism was focused on the fungal community that creates critical bioactive components. Bacterial community associated with Chinese Cordyceps has been previously described; however, most studies were only presenting direct comparisons in the Chinese Cordyceps and its microenvironments. In the current study, our objectives were to reveal the bacterial community structure composition and predict their function.

Immunosenescence refers to age-related declines in the capacity to respond to infections such as influenza (flu). Caloric restriction represents a known strategy to slow many aging processes, including those involving the immune system. More recently, some changes in the microbiome have been described with aging, while the gut microbiome appears to influence responses to flu vaccination and infection.

2-piperidone is a crucial industrial raw material of high-value nylon-5 and nylon-6,5. Currently, a major bottleneck in the biosynthesis of 2-piperidone is the identification of highly efficient 2-piperidone synthases. In this study, we aimed to identify specific strains among 51 human gut bacterial strains capable of producing 2-piperidone and to elucidate its synthetic mechanism.

Postnatal development of the human gut microbiota is linked to healthy growth. Because the number of potential interactions between community components is vast, an unanswered question is what mechanisms determine the form of community assembly (succession). We created a simplified, manipulable in vivo model where bacterial strains cultured from an infant were divided into consortia, representing earlier and later periods in assembly, and introduced in different order into germ-free mice fed infant formula. Measuring strain abundances, bacterial gene expression and levels of gut nutrients, and applying computational tools to deduce interacting features, we identify genomic and metabolic correlates of how strains establish and maintain themselves.

Quorum sensing is a cell-cell communication process that bacteria use to transition between individual and social lifestyles. In vibrios, homologous small RNAs called the Qrr sRNAs function at the center of quorum-sensing pathways.

Bacteria use a process of chemical communication called quorum sensing to assess their population density and to change their behavior in response to fluctuations in the cell number and species composition of the community. In this work, we identified the quorum-sensing-regulated proteome in the model organism Vibrio harveyi by bio-orthogonal non-canonical amino acid tagging (BONCAT). BONCAT enables measurement of proteome dynamics with temporal resolution on the order of minutes. We deployed BONCAT to characterize the time-dependent transition of V. harveyi from individual- to group-behaviors.

Quorum sensing is a chemical communication process that bacteria use to control collective behaviours including bioluminescence, biofilm formation, and virulence factor production. In Vibrio harveyi, five homologous small RNAs (sRNAs) called Qrr1–5, control quorum-sensing transitions. Here, we identify 16 new targets of the Qrr sRNAs. Mutagenesis reveals that particular sequence differences among the Qrr sRNAs determine their target specificities.

Regulated intramembrane proteolysis (RIP) by the Site-2 protease (S2P) results in the release of a transmembrane signaling protein. Curiously, however, S2P cleavage must be preceded by the action of the Site-1 protease (S1P). To decipher the underlying mechanism, we reconstituted sequential, in vitro cleavages of the Escherichia coli transmembrane protein RseA by DegS (S1P) and RseP (S2P). After DegS cleavage, the newly exposed carboxyl-terminal residue Val-148 of RseA plays an essential role for RseP cleavage, and its mutation to charged or dissimilar amino acids crippled the Site-2 cleavage. By contrast, the identity of residues 146 and 147 of RseA has no impact on Site-2 cleavage. These results explain why Site-1 cleavage must precede Site-2 cleavage.

A recent paper in Nature (Bae et al., 2022) reports the discovery of a phosphatidylethanolamine from Akkermansia muciniphila that mediates the immunomodulatory function of the bacterium via regulation of the Toll-like receptor 2 (TLR2) or the TLR2-TLR1 signaling complex in immune cells.

Bacterial motility is a vital aspect of human intestinal microbiome and is linked to disease pathogenesis and virulence. While intestinal ecosystem is a heterogeneous landscape, our understanding on bacterial movement patterns comes mainly from motility assays (swimming and swarming on agar plates) that lack the microstructural complexity of intestine. Moreover, pathophysiological conditions can alter the physical structure of microbial habitats. For instance, uniform mucus barrier in normal mucosa becomes defective and discontinuous with epithelial “obstacles” under inflammatory bowel disease (IBD) conditions. Hence, establishing a connection between physiological environments and the associated microbial motility is crucial to better understanding of microbiome-mediated inflammatory diseases and uncovering more promising treatment approaches.

Pharmacological activation of the xenobiotic-sensing nuclear receptors pregnane X receptor (PXR) and constitutive androstane receptor (CAR) is well-known to increase drug metabolism and reduce inflammation. Little is known regarding their physiological functions on the gut microbiome. In this study,

Recent evidence suggests that complex diseases can result from early life exposure to environmental toxicants. Polybrominated diphenyl ethers (PBDEs), and polychlorinated biphenyls (PCBs) are persistent organic pollutants (POPs) and remain a continuing risk to human health despite being banned from production. Developmental BPA exposure mediated-adult onset of liver cancer via epigenetic reprogramming mechanisms has been identified.

Bacterial motility under confinement is relevant to both environmental control and the spread of infection. Here, we report observations on Escherichia coli, Enterobacter sp., Pseudomonas aeruginosa, and Bacillus subtilis when they are confined within a thin layer of water around dispersed micrometer-sized particles sprinkled over a semisolid agar gel. In this setting, E. coli and Enterobacteria orbit around the dispersed particles. The liquid layer is shaped like a shallow tent with its height at the center set by the seeding particle, and the meniscus profile set by the strong surface tension of water. The tent-shaped confinement and the left handedness of the flagellar filaments result in exclusively clockwise circular trajectories. The thin fluid layer is resilient because of a balance between evaporation and reinforcement of fluid that permeated out of the agar.

The newly identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic respiratory disease. Moreover, thromboembolic events throughout the body, including in the CNS, have been described. Given the neurological symptoms observed in a large majority of individuals with COVID-19, SARS-CoV-2 penetrance of the CNS is likely. By various means, we demonstrate the presence of SARS-CoV-2 RNA and protein in anatomically distinct regions of the nasopharynx and brain. Furthermore, we describe the morphological changes associated with infection such as thromboembolic ischemic infarction of the CNS and present evidence of SARS-CoV-2 neurotropism.

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1,2,3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete.

Patient-derived 3D cell culture systems are currently advancing cancer research since they potentiate the molecular analysis of tissue-like properties and drug response under well-defined conditions. However, our understanding of the relationship between the heterogeneity of morphological phenotypes and the underlying transcriptome is still limited.

Integrative analysis of multi-omics layers at single cell level is critical for accurate dissection of cell-to-cell variation within certain cell populations. Here we report scCAT-seq, a technique for simultaneously assaying chromatin accessibility and the transcriptome within the same single cell. We show that the combined single cell signatures enable accurate construction of regulatory relationships between cis-regulatory elements and the target genes at single-cell resolution, providing a new dimension of features that helps direct discovery of regulatory patterns specific to distinct cell identities.

BioModels serves as a central repository of mathematical models representing biological processes. It offers a platform to make mathematical models easily shareable across the systems modelling community, thereby supporting model reuse. To facilitate hosting a broader range of model formats derived from diverse modelling approaches and tools, a new infrastructure for BioModels has been developed that is available at http://www.ebi.ac.uk/biomodels.

Decoding human genomic sequences requires comprehensive analysis of DNA sequence functionality. Through computational and experimental approaches, researchers have studied the genotype-phenotype relationship and generate important datasets that help unravel complicated genetic blueprints. Thus, the recently developed artificial intelligence methods can be used to interpret the functions of those DNA sequences.

Cell-type annotation is a critical step in single-cell data analysis. With the development of numerous cell annotation methods, it is necessary to evaluate these methods to help researchers use them effectively. Reference datasets are essential for evaluation, but currently, the cell labels of reference datasets mainly come from computational methods, which may have computational biases and may not reflect the actual cell-type outcomes. This study first constructed an experimentally labeled immune cell-subtype single-cell dataset of the same batch and systematically evaluated 18 cell annotation methods.

Radiomics can yield minable information from medical images, which can facilitate computer-aided diagnosis. However, the lack of repeatability and reproducibility of radiomic features (RFs) may hinder their generalizability in clinical applications.

The poor prognosis of hepatocellular carcinoma (HCC) calls for the development of accurate prognostic models. The growing number of studies indicating a correlation between autophagy activity and HCC indicates there is a commitment to finding solutions for the prognosis of HCC from the perspective of autophagy.

Papaya, a fruit crop cultivated in tropical and subtropical regions, is known for its nutritional benefits and medicinal applications. Here we report a 3× draft genome sequence of ‘SunUp’ papaya, the first commercial virus-resistant transgenic fruit tree1 to be sequenced. The papaya genome is three times the size of the Arabidopsis genome, but contains fewer genes, including significantly fewer disease-resistance gene analogues.

A set of 22 analogs of licochalcone A was designed and synthesized to explore their potentials as dipeptidyl peptidase 4 (DPP4) inhibitors with anti-inflammatory effects. The anti-DPP4 effects of these analogs were evaluated using the fluorescent substrate Gly-Pro-N-butyl-4-amino-1,8-naphthalimide (GP-BAN). The nitro-substituted analogue 27 exhibited the most potent activity (Ki = 0.96 μM). A structure–activity relationship investigation revealed that 4-hydroxyl and 5-chloro substituents are essential for DPP4 inhibition, while the 3′-nitro substituent improved both DPP4 inhibition and microsomal stability. Furthermore, compound 27 demonstrated good selectivity for DPP4 over other proteases,

The aim of this work was to highlight a considerable and broad problem in UGT1A10 activity assessment that has led to underestimation of its role in intestinal glucuronidation of drugs and other xenobiotics. The reason appears to be poor activity of the commercial UGT1A10 that is used by many laboratories, and here we have tested it by comparison with our recombinant His-tagged UGT1A10 (designated as UGT1A10-H), both expressed in insect cells. The glucuronidation rates of morphine, estradiol, estrone, SN-38, diclofenac, 4-methylumbelliferone, 7-amino-4-methylcoumarin, N-(3-carboxypropyl)-4-hydroxy-1,8-naphthalimide, and bavachinin were assayed.

A near-infrared fluorescent probe (DDAB) for highly selective and sensitive detection of carboxylesterase 2 (CE2) has been designed, synthesized, and systematically studied both in vitro and in vivo. Upon addition of CE2, the ester bond of DDAB could be rapidly cleaved and then release a near-infrared (NIR) fluorophore DDAO, which brings a remarkable yellow-to-blue color change and strong NIR fluorescence emission in physiological solutions.

In this study, a two-photon ratiometric fluorescent probe NCEN has been designed and developed for highly selective and sensitive sensing of human carboxylesterase 2 (hCE2) based on the catalytic properties and substrate preference of hCE2.

Illumina second generation sequencing is now an efficient route for generating enormous sequence collections that represent expressed genes and quantitate expression level. Taxus is a world-wide endangered gymnosperm genus and forms an important anti-cancer medicinal resource, but the large and complex genomes of Taxus have hindered the development of genomic resources. The research of its tissue-specific transcriptome is absent. There is also no study concerning the association between the plant transcriptome and metabolome with respect to the plant tissue type.

Host microbiota crosstalk is essential for the production and functional modulation of blood cell lineages. Whether, and if so how, the microbiota influences hematopoietic stem cells (HSCs) is unclear. Here, we show that the microbiota regulates HSC self-renewal and differentiation under stress conditions by modulating local iron availability in the bone marrow (BM). In microbiota-depleted mice, HSC self-renewal was enhanced during regeneration, while the commitment toward differentiation was dramatically compromised. Mechanistically,

Psychological stress has adverse effects on various human diseases, including those of the cardiovascular system. However, the mechanisms by which stress influences disease activity remain unclear. Here, using vaso-occlusive episodes (VOE) of sickle cell disease as a vascular disease model, we show that stress promoted VOE by eliciting a glucocorticoid hormonal response that augmented gut permeability, leading to microbiota-dependent interleukin-17A (IL-17A) secretion from T helper-17 (Th17) cells of the lamina propria, followed by the expansion of the circulating pool of aged neutrophils that triggered VOE.

The microbiota has emerged as an important regulator of the host immunity by the induction, functional modulation, or suppression of local and systemic immune responses. In return, the host immune system restricts translocation and fine tunes the composition and distribution of the microbiota to maintain a beneficial symbiosis. This paradigm applies to neutrophils, a critical component of the innate immunity, allowing their production and function to be influenced by microbial components and metabolites derived from the microbiota, and engaging them in the process of microbiota containment and regulation.

Perivascular mesenchymal stem and progenitor cells (MSPCs) are critical for forming a healthy hematopoietic stem cell (HSC) niche. However, the interactions and influence of acute myelogenous leukemia (AML) stem cells with the microenvironment remain largely unexplored. We have unexpectedly found that neuropathy of the sympathetic nervous system (SNS) promotes leukemic bone marrow infiltration in an MLL-AF9 AML model. Development of AML disrupts SNS nerves and the quiescence of Nestin+ niche cells, leading to an expansion of phenotypic MSPCs primed for osteoblastic differentiation at the expense of HSC-maintaining NG2+ periarteriolar niche cells. Adrenergic signaling promoting leukemogenesis is transduced by the β2, but not β3, adrenergic receptor expressed on stromal cells of leukemic bone marrow. These results indicate that sympathetic neuropathy may represent a mechanism for the malignancy in order to co-opt the microenvironment and suggest separate mesenchymal niche activities for malignant and healthy hematopoietic stem cells in the bone marrow.

The multistep sequence leading to leukocyte migration is thought to be locally regulated at the inflammatory site. Here, we show that broad systemic programs involving long-range signals from the sympathetic nervous system (SNS) delivered by adrenergic nerves regulate rhythmic recruitment of leukocytes in tissues. Constitutive leukocyte adhesion and migration in murine bone marrow (BM) and skeletal-muscle microvasculature fluctuated with circadian peak values at night. Migratory oscillations, altered by experimental jet lag, were implemented by perivascular SNS fibers acting on β-adrenoreceptors expressed on nonhematopoietic cells and leading to tissue-specific, differential circadian oscillations in the expression of endothelial cell adhesion molecules and chemokines.