Morozov, M. | bioRxiv Science

bioRxiv2025

MetaFX: feature extraction from whole-genome metagenomic sequencing data

MotivationMicrobial communities consist of thousands of microorganisms and viruses and have a tight connection with an environment, such as gut microbiota modulation of host body metabolism. However, the direct relationship between the presence of certain microorganism and host state often remains unknown. Toolkits using reference-based approaches are limited to microbes present in databases. Reference-free methods often require enormous resources for metagenomic assembly or results in many poorly interpretable features based on k-mers. ResultsHere we present MetaFX - an open-source library for feature extraction from whole-genome metagenomic sequencing data and classification of groups of samples. Using a large volume of metagenomic samples deposited in databases, MetaFX compares samples grouped by metadata criteria (e.g. disease, treatment, etc) and constructs genomic features distinct for certain types of communities. Features constructed based on statistical k-mer analysis and de Bruijn graphs partition. Those features are used in machine learning models for classification of novel samples. Extracted features can be visualised on de Bruijn graphs and annotated for providing biological insights. We demonstrate the utility of MetaFX by building classification models for 590 human gut samples with inflammatory bowel disease. Our results outperform the previous research disease prediction accuracy up to 17%, and improves classification results compared to taxonomic analysis by 9 {+/-} 10% on average. AvailabilityMetaFX is a feature extraction toolkit applicable for metagenomic datasets analysis and samples classification. The source code, test data, and relevant information for MetaFX are freely accessible at https://github.com/ctlab/metafx under the MIT License. Contactabivanov@itmo.ru

bioinformatics↗

bioRxiv2020

Fruit presence induces polar auxin transport in citrus and olive stem and represses hormone release from the bud

In many fruit trees, heavy fruit load in one year reduces flowering in the following year, creating a biennial fluctuation in yield termed alternate bearing (AB). In subtropical trees, where flowering induction is mostly governed by the accumulation of cold hours, fruit load is thought to generate a signal (AB signal) that blocks the perception of the cold induction. Fruit removal during a heavy-fruit-load year (On-Crop) is effective at inducing flowering only if performed one to a few months prior to onset of the flowering-induction period. We previously showed that following fruit removal, content of the auxin indoleacetic acid (IAA) in citrus buds is reduced, suggesting that the hormone plays a role in the AB signal. Here, we demonstrate that fruit presence generates relatively strong polar auxin transport (PAT) in citrus and olive stems. Upon fruit removal, PAT is reduced and allows auxin release from the bud. Furthermore, using immunolocalization, hormone and gene expression analyses, we show that in citrus, IAA level in the bud and, specifically, in the apical meristem is reduced upon fruit removal. Overall, our data provide support for the notion that fruit presence generates an auxin signal in the bud which may affect flowering induction. HIGHLIGHTSHeavy fruit load can reduce flowering intensity the following year. Fruit presence, inducing polar auxin transport in stems and inhibiting auxin release from buds, may be a fruit-load signal.

plant biology↗