以微生物之力重构健康生态的科学信仰

Motility is a fundamental characteristic of bacteria. Distinguishing between swarming and swimming, the two principal forms of bacterial movement, holds significant conceptual and clinical relevance. Conventionally, the detection of bacterial swarming involves inoculating samples on an agar surface and observing colony expansion, which is qualitative, time-intensive, and requires additional testing to rule out other motility forms.

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. SM3 and showed good performance when blindly tested on new swarming (positive) and swimming (negative) test images of SM3, achieving a sensitivity of 97.44% and a specificity of 100%.

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. Less studied, however, are the contrasts of collective motion between the swarming cells and their counterpart planktonic cells of comparable cell density.

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.We developed a polymicrobial plate agar assay to detect swarming and screened mice and humans with intestinal stress and inflammation.

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 latter is driven by the Laplace pressure caused by the concave meniscus. In short, we explain the physical mechanism of a convenient method to entrap bacteria within localized thin fluid film near a permeable surface.

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.

Versions Notes Abstract 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. Then, motif enrichment analysis identified some of the key motifs for circRNA formation. In conclusion, we designed deep learning network architecture suitable for learning gene sequences with sparse features and implemented it for the circRNA identification task, and the model has strong representation capability in the indication of some key loci.

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. Our findings revealed that four gut bacterial strains, namely Collinsella aerofaciens LFYP39, Collinsella intestinalis LFYP54, Clostridium bolteae LFYP116,

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. This approach may facilitate discoveries of how communities respond to various perturbations and microbiota-directed therapeutics.

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. The Qrr sRNAs regulate multiple mRNA targets including those encoding the quorum-sensing regulatory components luxR, luxO, luxM, and aphA.

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.

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.

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. Upon addition of hCE2, the probe could be readily hydrolyzed to release 4-amino-1,8-naphthalimide (NAH), which brings remarkable red-shift in fluorescence (90 nm) spectrum.

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.

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).

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. We showed that these rhythms have physiological consequences through alteration of hematopoietic cell recruitment and overall survival in models of septic shock, sickle cell vaso-occlusion, and BM transplantation. These data provide unique insights in the leukocyte adhesion cascade and the potential for time-based therapeutics for transplantation and inflammatory diseases.