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Many computational methods have been recently proposed to identify differentially abundant microbes related to a single disease; however, few studies have focused on large-scale microbe-disease association prediction using existing experimentally verified associations. This area has critical meanings. For example, it can help to rank and select potential candidate microbes for different diseases at-scale for downstream lab validation experiments and it utilizes existing evidence instead of the microbiome abundance data which usually costs money and time to generate.

We construct a multiplex heterogeneous network (MHEN) using human microbe-disease association database, Disbiome, and other prior biological databases, and define the large-scale human microbe-disease association prediction as link prediction problems on MHEN. We develop an end-to-end graph convolutional neural network-based mining model NinimHMDA which can not only integrate different prior biological knowledge but also predict different types of microbe-disease associations (e.g. a microbe may be reduced or elevated under the impact of a disease) using one-time model training. To the best of our knowledge, this is the first method that targets on predicting different association types between microbes and diseases. Results from large-scale cross validation and case studies show that our model is highly competitive compared to other commonly used approaches.

The codes are available at Github https//github.com/yuanjing-ma/NinimHMDA.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.

A rigorous yet general mathematical approach to mutagenesis, especially one capable of delivering systems-level perspectives would be invaluable. Such systems-level understanding of phage resistance is also highly desirable for phage-bacteria interactions and phage therapy research. Independently, the ability to distinguish between two graphs with a set of common or identical nodes and identify the implications thereof, is important in network science.

Herein we propose a measure called shortest path alteration fraction (SPAF) to compare any two networks by shortest paths, using sets. When SPAF is one, it can identify node pairs connected by at least one shortest path, which are present in either network but not both. Similarly, SPAF equaling zero identifies identical shortest paths, which are simultaneously present between a node pair in both networks. We study the utility of our measure theoretically in five diverse microbial species, to capture reported effects of well-studied mutations and predict newture. However, SPAF coherently identifies pairs of proteins at the end of a subset of shortest paths, from amongst hundreds of thousands of viable shortest paths in the networks. The altered functions associated with the protein pairs are strongly correlated with the observed phenotypes.The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a rapidly growing infectious disease, widely spread with high mortality rates. Since the release of the SARS-CoV-2 genome sequence in March 2020, there has been an international focus on developing target-based drug discovery, which also requires knowledge of the 3D structure of the proteome. Where there are no experimentally solved structures, our group has created 3D models with coverage of 97.5% and characterized them using state-of-the-art computational approaches. Models of protomers and oligomers, together with predictions of substrate and allosteric binding sites, protein-ligand docking, SARS-CoV-2 protein interactions with human proteins, impacts of mutations, and mapped solved experimental structures are freely available for download. These are implemented in SARS CoV-2 3D, a comprehensive and user-friendly database, available at https//sars3d.com/. This provides essential information for drug discovery, both to evaluate targets and design new potential therapeutics.Various proteins in plant chloroplasts are subject to thiol-based redox regulation, allowing light-responsive control of chloroplast functions. Most redox-regulated proteins are known to be reductively activated in the light in a thioredoxin (Trx)-dependent manner, but its regulatory network remains incompletely understood. Using a biochemical procedure, we here show that a specific form of phosphofructokinase (PFK) is a novel redox-regulated protein whose activity is suppressed upon the reduction. PFK is a key enzyme in the glycolytic pathway. In Arabidopsis thaliana, PFK5 is targeted to chloroplasts and uniquely contains an insertion sequence harboring two Cys residues (Cys152 and Cys157) in the N-terminal region. Redox shift assays using a thiol-modifying reagent indicated that PFK5 is efficiently reduced by a specific type of Trx, namely, Trx-f. PFK5 enzyme activity was lowered with the Trx-f-dependent reduction. PFK5 redox regulation was bidirectional; PFK5 was also oxidized and activated by the recently identified Trx-like2/2-Cys peroxiredoxin pathway. Mass spectrometry-based peptide mapping analysis revealed that Cys152 and Cys157 are critical for the intramolecular disulfide bond formation in PFK5. The involvement of Cys152 and Cys157 in PFK5 redox regulation was further supported by a site-directed mutagenesis study. PFK5 catalyzes the reverse reaction of fructose 1,6-bisphosphatase (FBPase), which is reduced and activated specifically by Trx-f. Our data suggest that PFK5 redox regulation, together with that of FBPase, constitutes a checkpoint for switching light/dark metabolism in chloroplasts.

Little is known about clinical characteristics and kidney outcome in patients with biopsy-proven immunoglobulin A nephropathy (IgAN) in a context of inflammatory bowel disease (IBD).

We conducted a retrospective multicenter study with centralized histological review, to analyze the presentation, therapeutic management and outcome of 24 patients suffering from IBD associated IgAN relative to a cohort of 134 patients with primary IgAN without IBD.

Crohn’s disease and ulcerative colitis accounted for 75% and 25% of IBD-associated IgAN cases, respectively. IBD was diagnosed before IgAN in 23 cases (a mean of 9 years previously) and was considered active at IgAN onset in 23.6% of patients. Hypertension was present in 41.7% of patients. Urinary protein-to-creatinine ratio exceeded 100 mg/mmol in 70.8% of patients (mean 254 mg/mmol). Selleckchem TW-37 Estimated glomerular filtration rate (eGFR) exceeded 60 ml/min/1.73m2 in 13/24 patients and only one patient required dialysis. In the Oxford MEST-C classification of renal biopsies, 57% were M1, 48% E1, 76% S1, 57% T1+T2 and 38% C1+C2.