Amod, A. | Search bioRxiv

bioRxiv2026

Identification of Human Gut Microbiome Derived Peptides Targeting Biofilm Specific Lectin Proteins of Pseudomonas aeruginosa

The carbohydrate-binding proteins (LecA and LecB) present within the extracellular polymeric substance (EPS) matrix of Pseudomonas aeruginosa play an essential role in maintaining the structural integrity of the biofilms through interactions with the EPS polysaccharides. Therefore, targeting the above lectins can turn out to be one of the promising strategies for disrupting P. aeruginosa biofilms. In the current study, we investigated the potency of antimicrobial peptides (AMPs) produced by the human gut microbiome in targeting LecA and LecB proteins of P. aeruginosa. Initially, a comprehensive in-silico pipeline was developed to identify and characterize putative antibacterial and antibiofilm AMPs produced by the human gut microbiome. These AMPs were then subsequently studied for their interaction with the lectin proteins through molecular docking, MM-GBSA, residue analysis, and molecular dynamics (MD) simulation. Among the studied peptides, amp21 and amp24 exhibited the strongest interactions with the lectin protein, occupying binding sites overlapping with key active-site residues previously reported for raffinose binding. amp6, amp21, and amp24 were selected for in vitro validation based on the MD simulation results of both LecA and LecB proteins. The above selected peptides exhibited minimal hemolytic activity across the tested concentration range. amp21 and amp6 were non-toxic to mammalian cells while amp24 demonstrated cytotoxicity only at higher doses. amp21 was found to be the most potent AMP and inhibited the growth of P. aeruginosa by [~]60% at 50 {micro}g mL{square}{superscript 1}. amp6 and amp21 resulted in a significant disruption of P. aeruginosa biofilms. Membrane permeabilization assays and scanning electron microscopy revealed that amp6, amp21, and amp24 damaged the bacterial cell membranes apart from compromising the integrity of the biofilm EPS matrix. Lastly, through in-silico studies, we designed ultrashort peptides (USPs) from the lead AMPs. The USPs (amp21.4 and amp24.2) exhibit superior antibiofilm efficacy compared to their parent AMPs. These findings establish human-gut microbiome-derived AMPs as promising candidates to target P. aeruginosa biofilms via inhibition of lectin proteins.

microbiology↗

bioRxiv2022

A Large-Scale ENIGMA Multisite Replication Study of Brain Age in Depression

BackgroundSeveral studies have evaluated whether depressed persons have older appearing brains than their nondepressed peers. However, the estimated neuroimaging-derived "brain age gap" has varied from study to study, likely driven by differences in training and testing sample (size), age range, and used modality/features. To validate our previously developed ENIGMA brain age model and the identified brain age gap, we aim to replicate the presence and effect size estimate previously found in the largest study in depression to date (N=2,126 controls & N=2,675 cases; +1.08 years [SE 0.22], Cohens d=0.14, 95% CI: 0.08-0.20), in independent cohorts that were not part of the original study. MethodsA previously trained brain age model (www.photon-ai.com/enigma_brainage) based on 77 FreeSurfer brain regions of interest was used to obtain unbiased brain age predictions in 751 controls and 766 persons with depression (18-75 years) from 13 new cohorts collected from 20 different scanners. ResultsOur ENIGMA MDD brain age model generalized reasonably well to controls from the new cohorts (predicted age vs. age: r = 0.73, R2=0.47, MAE=7.50 years), although the performance varied from cohort to cohort. In these new cohorts, on average, depressed persons showed a significantly higher brain age gap of +1 year (SE 0.35) (Cohens d{square}={square}{square}.15, 95% CI: 0.05-0.25) compared with controls, highly similar to our previous finding. ConclusionsThis study further validates our previously developed ENIGMA brain age algorithm. Importantly, we replicated the brain age gap in depression with a comparable effect size. Thus, two large-scale independent mega-analyses across in total 32 cohorts and >3,400 patients and >2,800 controls worldwide show reliable but subtle effects of brain aging in adult depression.

neuroscience↗