Biology subjects

Meirkhanova, A.

Publications and source records attributed to Meirkhanova, A..

4 recordsLinked to original sources

bioRxiv2024

Spectral algal fingerprinting and long sequencing in synthetic algal-microbial communities

O_LISynthetic biology has made progress in creating artificial microbial and algal communities, but technical and evolutionary complexities still pose significant challenges. C_LIO_LITraditional methods for studying microbial and algal communities, such as microscopy and pigment analysis, are limited in throughput and resolution. In contrast, advancements in full-spectrum cytometry enabled high-throughput, multidimensional analysis of single cells based on their size, complexity, and spectral fingerprints, offering more precise and comprehensive analysis than conventional flow cytometry. C_LIO_LIThis study demonstrates the use of full-spectrum cytometry for analyzing synthetic algal-microbial communities, facilitating rapid species identification and enumeration. The workflow involves recording individual spectral signatures from monocultures, utilizing autofluorescence to distinguish them from noise, and subsequent creation of a spectral library for further analysis. The obtained library is used then to analyze mixtures of unicellular cyanobacteria and synthetic phytoplankton communities, revealing differences in spectral signatures. The synthetic consortium experiment monitored algal growth, comparing results from different instruments and highlighting the advantages of the spectral virtual filter system for precise population separation and abundance tracking. This approach demonstrated higher flexibility and accuracy in analyzing multi-component algal-microbial assemblages and tracking temporal changes in community composition. C_LIO_LIBy capturing the complete emission spectrum of each cell, this method enhances the understanding of algal-microbial community dynamics and responses to environmental stressors. With development of standardized spectral libraries, our work demonstrates an improved characterization of algal communities, advancing research in synthetic biology and phytoplankton ecology. C_LI

ecology↗

bioRxiv2023

Species-level classification provides new insights into the biogeographical patterns of microbial communities in shallow saline lakes

Saline lakes are rapidly drying out across the globe, particularly in Central Asia, due to climate change and anthropogenic activities. We present the results of a long-read next generation sequencing analysis of the 16S rRNA-based taxonomic structure of bacteriomes of the Tengiz-Korgalzhyn lakes system. We found that the shallow endorheic, mostly saline lakes of the system show unusually low bacterioplankton dispersal rates at species-level taxonomic resolution. The major environmental factor structuring the lakes microbial communities was salinity. The dominant bacterial phyla of the lakes with high salinity included a significant proportion of marine and halophilic species. In sum, these results, which can be applied to other lake systems of the semi-arid regions, improve our understanding of the factors influencing lake microbiomes undergoing salinization in response to climate change and other anthropogenic factors. Our results show that finer taxonomic classification can provide new insights and improve our understanding of the environmental factors influencing the microbiomes of lakes undergoing salinization in response to climate change and other anthropogenic factors.

ecology↗

bioRxiv2023

Dynamics of associated microbiomes during algal bloom development: to see and to be seeing

Our understanding of the interactions between bacteria and phytoplankton in the freshwater phycosphere, including the development of algal blooms, is very limited. To identify the taxa and compositional variation within microbial communities, we performed 16S rRNA amplicon sequencing research on samples collected weekly through summer from mesocosms that differed in temperature and mixing regimes. We investigated, for the first time, the abundance diversity of microalgae, including Chlorophyta, Cryptophyta, and Cyanobacteria species, using visualization-based FlowCAM analysis and classification of microbial communities to species level by nanopore next-generation sequencing. We found that nanopore metagenomics, in parallel with complementary imaging flow cytometry, can depict the fine temporal dynamics of microbiomes associated with visually identified Microcystis morphospecies, Chlorophyta, and Cryptophyta during algal bloom development. Our results showed that the temporal characteristics of microbiomes combined with a visual approach may be a key tool to predict the metacommunity structure and dynamics of algal blooms in response to anthropogenic effects and climate change.

microbiology↗

bioRxiv2022

Long-term temperature trend in Kamchatka supports expansion of harmful algae

Ocean coastal ecosystems are changing, and global shifts in temperature lead to the expansion and intensification of harmful algae. In conjunction with anthropogenic effects it may result in future exacerbation of harmful algal blooms. Here we use the 2002-2020 years record of surface ocean temperature data retrieved from Sentinel-2 satellite to examine the recent temperature trend in Avacha Bay, Kamchatka Peninsula. Satellite analysis demonstrated a temperature increase trend in ocean surface water during spring and summer months and detected algal bloom in July 2020 preceding a mass death of marine benthic life in September-October 2020. Using 16S rRNA and 18S rRNA gene amplicon nanopore-based sequencing, we analyzed microbial and microalgal communities in the water samples from area of 2020 algal blooms. Our results suggest the presence of potentially toxic and bloom-forming algae from genera related to former HABs (harmful algal blooms) in the Avacha Bay region. A better understanding of the potentially toxic algae phytoplankton composition in the shifting temperature environment and time-series monitoring of HABs is of utmost importance for scientific community. We suggest that satellite analysis in combination with eDNA monitoring by nanopore-based sequencing represents promising option to detect potentially toxic algae and follow bloom development.

ecology↗