Passage of light through a suspension is accompanied by a competition of processes of absorption and scattering for each individual particle. As a result, a hypochromism phenomenon (a decrease in the extinction coefficient) takes place. The hypochromism value increases with the growth of a particle sizes or its refractive index. Since Tyndall’s light scattering in a suspension where the size of every particle is considerably larger than the wavelength weakly depends on the wavelength, the absorption (or excitation) spectrum is almost uniformly attenuated. A simple method for determination of the true extinction coefficients of the absorption and excitation spectra of diluted suspensions which have no multiple light scattering is proposed. Experimental data on the spectra of hemoglobin in erythrocytes, actinomycin in DNA, and flavines in mitochondria are discussed.

Beneficial properties of lactic acid bacteria have been known long ago, but particular interest in probiotics has arisen in the last two decades due to the understanding of the important role of intestinal microflora in human life. Thus, the ability of probiotics to support healthy homeostasis of gut microbiomes has received particular attention. Here, we evaluated the effect of a probiotic consisting of Bifidobacterium longum and Lacticaseibacillus paracasei on the gut microbiome of male rats, assessed their persistence in the fecal biota, and compared probiotic-mediated changes in vitro and in vivo. As expected, microbiomes of two enterotypes were identified in the feces of 21 animals, and it turned out that even a single dose of the probiotic altered the microbial composition. Upon repeated administration, the E1 biota temporarily acquired properties of the E2 type. Being highly sensitive to the intervention of probiotic bacteria at the phylum and genus levels, the fecal microbiomes retained the identity of their enterotypes when transferred to a medium optimized for gut bacteria. For the E2 biota, even similarities between probiotic-mediated reactions in vitro and in vivo were detected. Therefore, fecal-derived microbial communities are proposed as model consortia to optimize the response of resident bacteria to various agents.

Alignment-free approaches employing short k-mers as barcodes for individual genomes have created a new strategy for taxonomic analysis and paved a way for high-resolution phylogeny. Here, we introduce this strategy for the Lacticaseibacillus paracasei species as a taxon requiring barcoding support for precise systematics. Using this approach for phylotyping of L. paracasei VKM B-1144 at the genus level, we identified four L. paracasei phylogroups and found that L. casei 12A belongs to one of them, rather than to the L. casei clade. Therefore, we propose to change the specification of this strain. At the genus level we found only one relative of L. paracasei VKM B-1144 among 221 genomes, complete or available in contigs, and showed that the coding potential of the genome of this “rare” strain allows its consideration as a potential probiotic component. Four sets of published metagenomes were used to assess the dependence of L. paracasei presence in the human gut microbiome on chronic diseases, dietary changes and antibiotic treatment. Only antibiotics significantly affected their presence, and strain-specific barcoding allowed the identification of the main scenarios of the adaptive response. Thus, suggesting bacteria of this species for compensatory therapy, we also propose strain-specific barcoding for selecting optimal strains for target microbiomes.

The study of tumor-associated microbiomes using whole-genome sequencing (WGS) has attracted considerable attention, but microbial signal detection remains controversial due to host contamination and methodological artifacts. As the necessity of human-read removal becomes increasingly evident, many groups now include this step in their data pre-processing workflows. In this work, we introduce an open-source tool, HumanFilt, designed for rigorous host-read removal and apply it to the re-analysis of WGS data from 10 mucinous rectal adenocarcinoma cases originally published by Reynolds et al. The workflow integrates k-mer-based classification (Kraken2), quality and adapter trimming (Trim Galore), vector filtering (BBDuk/UniVec_Core), and duplicate removal (FastUniq). After reducing data complexity, a multi-aligner, multi-reference approach (BWA-MEM/GRCh38, Bowtie2/T2T-CHM13, and Minimap2/Human Pangenome Reference Consortium v1.1) removes remaining host sequences, collectively eliminating more than 99.9% of human-derived reads. Although the additional alignment steps eliminated only a small fraction of total reads, they consistently removed millions of residual sequences per sample, underscoring the importance of rigorous filtering in data sets where non-human reads are a small minority. Taxonomic profiling with PathSeq and MetaPhlAn revealed reproducible enrichment of Fusobacterium species in tumor versus matched normal tissues, and comparison before and after filtering showed that this tumor-over-normal pattern was preserved despite an overall reduction in RPM values. Simulation analyses further showed that HumanFilt preserved more than 99.7% of true Fusobacterium signals, supporting high specificity without meaningful false-negative loss of microbial reads. In direct comparison with Deacon and NoHuman, HumanFilt achieved the most stringent host-read removal but also removed a greater proportion of PathSeq-classified Fusobacterium reads, highlighting the trade-off between maximal host depletion and preservation of ambiguous microbial signal. Cross-validation with immunofluorescence analysis using pan- Fusobacterium (detecting both Fusobacterium animalis and Fusobacterium nucleatum ) and F. nucleatum -specific antibodies showed general consistency with Fusobacterium subspecies detected by WGS. Compared to the unfiltered analysis, host depletion markedly reduced artificial microbial signals in normal samples while preserving tumor-associated Fusobacterium , resulting in a more reliable microbial profile. IMPORTANCE: We developed an open-source tool that enables rapid removal of human-derived sequences and applied it to rectal cancer whole-genome sequencing data. This approach reduced false microbial signals while preserving true tumor-associated Fusobacterium , and simulation analyses showed that it retained more than 99.7% of true Fusobacterium reads. Comparison with Deacon and NoHuman showed that HumanFilt achieved more stringent host depletion but also highlighted the trade-off between aggressive host filtering and preservation of ambiguous microbial signal. We also observed general consistency between the sequencing results and immunofluorescence staining in tissue. Together, these findings provide a more reliable basis for studying tumor-bacteria interactions.

The development of alignment-free approaches using short k-mers as barcodes has revo-lutionized taxonomic analysis, enabling bacterial identification at the phylogroup level even within natural communities. We applied this approach to characterize Escherichia coli intraspecific diversity in human gut microbiomes using publicly available datasets. By estimating the relative abundance of eight E. coli phylogroups defined by their 18-mer markers in 558 fecal samples, we employed correlation analysis and machine learning techniques to assess the discriminatory power of their patterns under different host phys-iological states. We compared E. coli phylogroup distribution between microbiomes of healthy individuals and patients with chronic colorectal disorders, tracked their dynamic alterations following prolonged antibiotic exposure with subsequent probiotic-assisted recovery, and evaluated changes induced by a physiologically beneficial dietary interven-tion for obesity. As a result, binary classification methods distinguished most compared datasets, while correlation analysis revealed shifts in phylogroups connectivity networks and their bimodal interactions with Prevotella, suggesting intra- and inerspecific epistatic relationships. Finally, a technique based on nonlinear dimensionality reduction visual-ized all distinct clusters of all sets, providing a chance to test the feasibility of using intra-specific phylotyping of E. coli for medical applications.