Complement in breast milk modifies offspring gut microbiota to promote infant health.

Breastfeeding offers demonstrable benefits to newborns and infants by providing nourishment and immune protection and by shaping the gut commensal microbiota. Although it has been appreciated for decades that breast milk contains complement components, the physiological relevance of complement in breast milk remains undefined. Here, we demonstrate that weanling mice fostered by complement-deficient dams rapidly succumb when exposed to murine pathogen Citrobacter rodentium (CR), whereas pups fostered on complement-containing milk from wild-type dams can tolerate CR challenge. The complement components in breast milk were shown to directly lyse specific members of gram-positive gut commensal microbiota via a C1-dependent, antibody-independent mechanism, resulting in the deposition of the membrane attack complex and subsequent bacterial lysis. By selectively eliminating members of the commensal gut community, complement components from breast milk shape neonate and infant gut microbial composition to be protective against environmental pathogens such as CR.

RVdb: a comprehensive resource and analysis platform for rhinovirus research.

Rhinovirus (RV), a prominent causative agent of both upper and lower respiratory diseases, ranks among the most prevalent human respiratory viruses. RV infections are associated with various illnesses, including colds, asthma exacerbations, croup and pneumonia, imposing significant and extended societal burdens. Characterized by a high mutation rate and genomic diversity, RV displays a diverse serological landscape, encompassing a total of 174 serotypes identified to date. Understanding RV genetic diversity is crucial for epidemiological surveillance and investigation of respiratory diseases. This study introduces a comprehensive and high-quality RV data resource, designated RVdb (http://rvdb.mgc.ac.cn), covering 26 909 currently identified RV strains, along with RV-related sequences, 3D protein structures and publications. Furthermore, this resource features a suite of web-based utilities optimized for easy browsing and searching, as well as automatic sequence annotation, multiple sequence alignment (MSA), phylogenetic tree construction, RVdb BLAST and a serotyping pipeline. Equipped with a user-friendly interface and integrated online bioinformatics tools, RVdb provides a convenient and powerful platform on which to analyse the genetic characteristics of RVs. Additionally, RVdb also supports the efforts of virologists and epidemiologists to monitor and trace both existing and emerging RV-related infectious conditions in a public health context.

A deep learning method to predict bacterial ADP-ribosyltransferase toxins.

MOTIVATION: ADP-ribosylation is a critical modification involved in regulating diverse cellular processes, including chromatin structure regulation, RNA transcription, and cell death. Bacterial ADP-ribosyltransferase toxins (bARTTs) serve as potent virulence factors that orchestrate the manipulation of host cell functions to facilitate bacterial pathogenesis. Despite their pivotal role, the bioinformatic identification of novel bARTTs poses a formidable challenge due to limited verified data and the inherent sequence diversity among bARTT members. RESULTS: We proposed a deep learning-based model, ARTNet, specifically engineered to predict bARTTs from bacterial genomes. Initially, we introduced an effective data augmentation method to address the issue of data scarcity in training ARTNet. Subsequently, we employed a data optimization strategy by utilizing ART-related domain subsequences instead of the primary full sequences, thereby significantly enhancing the performance of ARTNet. ARTNet achieved a Matthew's correlation coefficient (MCC) of 0.9351 and an F1-score (macro) of 0.9666 on repeated independent test datasets, outperforming three other deep learning models and six traditional machine learning models in terms of time efficiency and accuracy. Furthermore, we empirically demonstrated the ability of ARTNet to predict novel bARTTs across domain superfamilies without sequence similarity. We anticipate that ARTNet will greatly facilitate the screening and identification of novel bARTTs from bacterial genomes. AVAILABILITY AND IMPLEMENTATION: ARTNet is publicly accessible at http://www.mgc.ac.cn/ARTNet/. The source code of ARTNet is freely available at https://github.com/zhengdd0422/ARTNet/.

Nanochannel Stability of Chemically Converted Graphene Oxide Membranes.

Chemically converted graphene oxide laminate membranes, which exhibit stable interlayered nanochannels in aqueous environments, are receiving increasing attention owing to their potential for selective water and ion permeation. However, how the molecular properties of conversion agents influence the stabilization of nanochannels and how effectively nanochannels are stabilized have rarely been studied. In this study, mono-, di-, and tri-saccharide molecules of glucose (Glu), maltose (Glu2), and maltotriose (Glu3) are utilized, respectively, to chemically modify graphene oxide (GO). The aim is to create nanochannels with different levels of stability and investigate how these functional conversion agents affect the separation performance. The effects of the property differences between different conversion agents on nanochannel stabilization are demonstrated. An agent with efficient chemical reduction of GO and limited intercalation in the resulting nanochannel ensures satisfactory nanochannel stability during desalination. The stabilized membrane nanochannel exhibits a permeance of 0.69 L m-2 h-1 bar-1 and excellent Na2SO4 rejection of 96.42%. Furthermore, this optimized membrane nanochannel demonstrates enhanced stability under varying external conditions compared to the original GO. This study provides useful information for the design of chemical conversion agents for GO nanochannel stabilization and the development of nanochannel membranes for precise separation.

Integrating plasma protein-centric multi-omics to identify potential therapeutic targets for pancreatic cancer.

BACKGROUND: Deciphering the role of plasma proteins in pancreatic cancer (PC) susceptibility can aid in identifying novel targets for diagnosis and treatment. METHODS: We examined the relationship between genetically determined levels of plasma proteins and PC through a systemic proteome-wide Mendelian randomization (MR) analysis utilizing cis-pQTLs from multiple centers. Rigorous sensitivity analyses, colocalization, reverse MR, replications with varying instrumental variable selections and additional datasets, as well as subsequent meta-analysis, were utilized to confirm the robustness of significant findings. The causative effect of corresponding protein-coding genes' expression and their expression pattern in single-cell types were then investigated. Enrichment analysis, between-protein interaction and causation, knock-out mice models, and mediation analysis with established PC risk factors were applied to indicate the pathogenetic pathways. These candidate targets were ultimately prioritized upon druggability and potential side effects predicted by a phenome-wide MR. RESULTS: Twenty-one PC-related circulating proteins were identified in the exploratory phase with no evidence for horizontal pleiotropy or reverse causation. Of these, 11 were confirmed in a meta-analysis integrating external validations. The causality at a transcription level was repeated for neutrophil elastase, hydroxyacylglutathione hydrolase, lipase member N, protein disulfide-isomerase A5, xyloside xylosyltransferase 1. The carbohydrate sulfotransferase 11 and histo-blood group ABO system transferase exhibited high-support genetic colocalization evidence and were found to affect PC carcinogenesis partially through modulating body mass index and type 2 diabetes, respectively. Approved drugs have been established for eight candidate targets, which could potentially be repurposed for PC therapies. The phenome-wide investigation revealed 12 proteins associated with 51 non-PC traits, and interference on protein disulfide-isomerase A5 and cystatin-D would increase the risk of other malignancies. CONCLUSIONS: By employing comprehensive methodologies, this study demonstrated a genetic predisposition linking 21 circulating proteins to PC risk. Our findings shed new light on the PC etiology and highlighted potential targets as priorities for future efforts in early diagnosis and therapeutic strategies of PC.

The association between the basal metabolic rate and cardiovascular disease: A two-sample Mendelian randomization study.

BACKGROUND: Mendelian randomization analysis was applied to elucidate the causal relationship between the basal metabolic rate (BMR) and common cardiovascular diseases. METHOD: We choose BMR as exposure. BMR is the metabolic rate of the body when the basic physiological activities (blood circulation, breathing and constant body temperature) are maintained. The normal BMR is 1507 kcal/day for men and 1276 kcal/day for women. The dataset was drawn from the public GWAS dataset (GWAS ID: ukb-a-268), collected and analysed by UK biobank, containing 331,307 European males and females. SNPs independently and strongly associated with BMR were used as instrumental variables in the inverse variance weighted analysis. MR-Egger, weighted median, MR pleiotropy residual sum, and outlier methods were also performed, and the sensitivity was evaluated using horizontal pleiotropy and heterogeneity analyses to ensure the stability of the results. RESULTS: An increased BMR is associated with a higher risk of cardiomyopathy (odds ratio [OR] = 2.00, 95% confidence interval [CI], 1.57-2.54, p = 1.87 × 10-8), heart failure (OR = 1.39, 95% CI, 1.27-2.51, p = 8.1 × 10-13), and valvular heart disease (OR = 1.18, 95% CI, 1.10-1.27, p = .00001). However, there was no clear association between BMR and the subtypes of other cardiovascular diseases, such as coronary disease (OR = .96, 95% CI, .85-1.08, p = .48651) and atrial fibrillation (AF) (OR = 1.85, 95% CI, 1.70-2.02, p = 6.28 × 10-44). CONCLUSION: Our study reveals a possible causal effect of BMR on the risk of cardiomyopathy, heart failure and valvular disease, but not for coronary disease and AF.

Two-dimensional angle measurement with sub-arcsecond precision and MHz update rate using heterodyne interferometry with optical frequency comb.

Heterodyne interferometry is a powerful tool for achieving high precision and fast measurement. We developed an angle measurement system based on heterodyne interferometry by combining discrete equal-spacing longitudinal modes of optical frequency comb with an acousto-optic modulator. Using a self-designed grating-corner-cube sensor, this method can achieve a two-dimensional angle measurement with sub-arcsecond accuracy and megahertz (MHz) update rate. We experimentally demonstrate a precision of 0.073 arcsec under a 3 MHz update rate, and comparison residuals are kept within 0.063 arcsec over 300 arcsec when compared to a piezo stage. In the dynamic measurement of a 40 Hz frequency, the continuous sinusoidal motion of 0.05 arcsec can be clearly distinguished and reconstructed.

Nesfatin-1: A Biomarker and Potential Therapeutic Target in Neurological Disorders.

Nesfatin-1 is a novel adipocytokine consisting of 82 amino acids with anorexic and anti-hyperglycemic properties. Further studies of nesfatin-1 have shown it to be closely associated with neurological disorders. Changes in nesfatin-1 levels are closely linked to the onset, progression and severity of neurological disorders. Nesfatin-1 may affect the development of neurological disorders and can indicate disease evolution and prognosis, thus informing the choice of treatment options. In addition, regulation of the expression or level of nesfatin-1 can improve the level of neuroinflammation, apoptosis, oxidative damage and other indicators. It is demonstrated that nesfatin-1 is involved in neuroprotection and may be a therapeutic target for neurological disorders. In this paper, we will also discuss the role of nesfatin-1 as a biomarker in neurological diseases and its potential mechanism of action in neurological diseases, providing new ideas for the diagnosis and treatment of neurological diseases.

Silencing of the T-type voltage-gated calcium channel α1 subunit by fungus-mediated RNAi altered the structure of F-actin and caused defective behaviors in Ditylenchus destructor.

BACKGROUND: T-type calcium channels, characterized as low-voltage activated (LVA) calcium channels, play crucial physiological roles across a wide range of tissues, including both the neuronal and nonneuronal systems. Using in situ hybridization and RNA interference (RNAi) techniques in vitro, we previously identified the tissue distribution and physiological function of the T-type calcium channel α1 subunit (DdCα1G) in the plant-parasitic nematode Ditylenchus destructor. METHODS AND RESULTS: To further characterize the functional role of DdCα1G, we employed a combination of immunohistochemistry and fungus-mediated RNAi and found that DdCα1G was clearly distributed in stylet-related tissue, oesophageal gland-related tissue, secretory-excretory duct-related tissue and male spicule-related tissue. Silencing DdCα1G led to impairments in the locomotion, feeding, reproductive ability and protein secretion of nematodes. To confirm the defects in behavior, we used phalloidin staining to examine muscle changes in DdCα1G-RNAi nematodes. Our observations demonstrated that defective behaviors are associated with related muscular atrophy. CONCLUSION: Our findings provide a deeper understanding of the physiological functions of T-type calcium channels in plant-parasitic nematodes. The T-type calcium channel can be considered a promising target for sustainable nematode management practices.

ZOVER: the database of zoonotic and vector-borne viruses.

Emerging infectious diseases significantly threaten global public health and socioeconomic security. The majority of emerging infectious disease outbreaks are caused by zoonotic/vector-borne viruses. Bats and rodents are the two most important reservoir hosts of many zoonotic viruses that can cross species barriers to infect humans, whereas mosquitos and ticks are well-established major vectors of many arboviral diseases. Moreover, some emerging zoonotic diseases require a vector to spread or are intrinsically vector-borne and zoonotically transmitted. In this study, we present a newly upgraded database of zoonotic and vector-borne viruses designated ZOVER (http://www.mgc.ac.cn/ZOVER). It incorporates two previously released databases, DBatVir and DRodVir, for bat- and rodent-associated viruses, respectively, and further collects up-to-date knowledge on mosquito- and tick-associated viruses to establish a comprehensive online resource for zoonotic and vector-borne viruses. Additionally, it integrates a set of online visualization tools for convenient comparative analyses to facilitate the discovery of potential patterns of virome diversity and ecological characteristics between/within different viral hosts/vectors. The ZOVER database will be a valuable resource for virologists, zoologists and epidemiologists to better understand the diversity and dynamics of zoonotic and vector-borne viruses and conduct effective surveillance to monitor potential interspecies spillover for efficient prevention and control of future emerging zoonotic diseases.