Biology subjects

Barteneva, N. S.

Publications and source records attributed to Barteneva, N. S..

11 recordsLinked to original sources

bioRxiv2026

Global assessment of wildlife cryopreservation reveals major taxonomic gaps and strong species-specific differences in mammalian sperm cryotolerance

Currently, global conservation efforts for wildlife focus on a limited number of cell types and species. Although protocols from domestic and non-threatened related species have been applied to endangered species, cryopreservation techniques are species-specific and are constrained by a lack of understanding of reproductive biology in these species. Based on a review of 126 original studies from 27 countries, encompassing 160 species, we assess the current state of cryopreservation in wildlife, including gametes, embryos, somatic cells, and various tissues. Furthermore, we focused on the most homogeneous and frequently studied cell type in wildlife cryobanking: mammals sperm.. A meta-analysis of 27 studies was conducted to examine species-specific and protocol-dependent factors that affect post-thaw sperm quality. Our findings provide quantitative estimates of cryopreservation for various cell types and tissues in wildlife taxa. Furthermore, they serve as a crucial research roadmap, identifying major challenges in cryopreservation and proposing solutions.

physiology↗

bioRxiv2025

Analysis of microalgae autofluorescence using full-spectrum cytometry to discriminate and monitor microalgae and bacteria

AbstractThe autofluorescence of algal pigments allows for non-invasive, high-throughput characterization of microalgae at a single-cell resolution. We applied full-spectrum cytometry, imaging flow cytometry, and cell sorting to analyze the spectral and morphological diversity among major microalgal groups and 102 Chlorophyta strains. The distinct spectral signatures from chlorophylls, carotenoids, and phycobiliproteins enabled us to achieve taxonomic resolution with clear separation of phycobiliprotein-containing taxa. Furthermore, principal component analysis of Volvocales revealed three spectral clusters supported by corresponding differences in cell size and shape. Additionally, in Gonium cultures, we observed that spectral signatures in the yellow-green region were altered by bacterial presence, suggesting that interactions between algal host and bacteria affect pigment-related fluorescence. Spectral heterogeneity observed within monocultures was linked to pigment accumulation, cell size, and morphological variability. These findings establish full-spectrum cytometry as a powerful method for profiling pigment composition, physiology, and structural diversity in microalgae, with broad applications in microbial ecology, environmental monitoring, and biotechnology.

microbiology↗

bioRxiv2025

Deep Learning-enabled Sperm Morphology Analysis of Bovine Sperm for label-free Imaging Flow Cytometry

Data analysis of sperm morphology is critical for evaluating bull fertility, yet it is often performed using light microscopy and staining techniques in a highly subjective and manual manner. In this study, we introduce a scalable, high-resolution approach combining label-free Imaging Flow Cytometry (IFC) with deep learning for automated classification of bovine sperm morphology. We analyzed 436,374 single-cell images obtained from three prominent bull breeds in Kazakhstan - Kazakh Whitehead, Auliekol, and Simmental from fresh and cryopreserved sperm - providing a uniquely large and diverse dataset. The dataset was used for training and evaluation of deep learning models, among which the convolutional neural network (CNN) MobileNetV4 yielded superior results, achieving 92.3% accuracy and a 0.91 F1-score after training with a Layer-wise Pretraining and Fine-Tuning (LP-FT) strategy. The model classified spermatozoa into eight distinct morphological categories. The CNN-based pipeline ensured consistent, observer-independent classification across all samples. Testing across different conditions and breeds resulted in a 5-10% drop in generalization performance, highlighting the impact of domain-specific biases and underscoring the need for larger, standardized datasets. The proportion of morphologically abnormal spermatozoa varied between seasons and after cryopreservation. This study highlights the advantages of integrating IFC and artificial intelligence (AI) algorithms for robust, high-throughput, and objective label- free spermatozoa morphology assessment in fresh and cryopreserved sperm, offering a promising tool for improving fertility diagnostics and breeding strategies in veterinary practice.

systems biology↗

bioRxiv2024

Assessing Aral Sea residual lake system: impact of fluctuating salinity on phytoplankton communities

The Aral Sea was once the fourth-largest inland water body in the world. However, the lake rapidly shrank over the past six decades, mainly due to the loss of inflow from one of its tributaries, the Amu Darya River. Lakes and reservoirs are traditionally characterized by static chemical and morphological parameters, leaving untouched a dynamic impact of phytoplankton changes. We used an integrated approach combining traditional microscopy and FlowCam-based imaging flow cytometry to study phytoplankton communities during the 2018 and 2019 expeditions in the Aral Sea remnant lakes system. The residual Aral Sea water bodies experienced different environmental conditions, forming hypersaline South Aral, North Aral Sea that is constantly getting freshwater, and brackish Chernyshev Bay and Tushchybas Lake with 2-8 times amplitude of salinity changes attributed to the variability in the precipitation and periodical influx of freshwater. The salinity fluctuations had an impact on the phytoplankton communities in Chernyshev Bay, making it similar to the phytoplankton of North Aral in 2018 while resembling the hypersaline South Aral phytoplankton assemblages in 2019. Multivariate analysis revealed that salinity, water temperature, ammonium, and nitrates were major contributors to explaining the variance in the sampling data. We conclude that drastic phytoplankton fluctuations occur in the two brackish water bodies in the middle of the former Aral Sea, reflecting changes in salinity.

ecology↗

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↗

bioRxiv2024

A matter of salt: global assessment of the effect of salt ionic composition as a driver of aquatic bacterial diversity

While the strong general effects of salinity on microbial diversity are well-known and described for marine and freshwater habitats, the impact of the specific composition of major inorganic ions remains largely unexplored. In this study, we assess how microbial community structure in inland saline aquatic habitats is influenced by ionic composition as compared to salinity, spatial factors, and other environmental parameters. We collected and analysed 16S rRNA gene V4 and V3-V4 amplicon datasets from freshwater to hypersaline aquatic environments worldwide (in total 375 samples from 130 lakes). With an emphasis on saline inland waters characterised by highly variable ionic composition, we demonstrated that the ionic composition of the major ions explained more variability in community composition than bulk salinity and that the geographic location of the sampling sites had only an ambiguous effect. We also identified the taxa contributing the most to the observed dissimilarity between communities from sites with different ionic composition and found mostly lineages known to be characteristic for a given habitat type, such as Actinobacteria acI in freshwater, Halomonadaceae in saline, or Nitriliruptorales in soda and soda-saline habitats. Many of these habitat type-specific indicator lineages were monophyletic, underpinning ionic composition as a crucial eco-evolutionary driver of aquatic microbial diversity.

microbiology↗

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↗

bioRxiv2023

From colonial clusters to colonial "sheaths": analysis of Microcystis morphospecies in mesocosm by imaging flow cytometry

The alarming increase in the frequency of blooms of Microcystis in freshwater lakes and reservoirs occurs worldwide, with major implications for their ecosystem functioning and water quality. We applied FlowCAM-based imaging flow cytometry together with PCR and sequencing to get a comprehensive picture of the seasonal development of Microcystis community in a long-term running lake mesocosm experiment. The IFC analysis with manual taxonomic classification confirmed early findings with a machine learning algorithm that some Microcystis morphospecies completely disappeared and re-appeared along the mesocosm experiment timeline. This observation supports the hypothesis of the main transition pathways of colonial Microcystis. For the first time, colonial mucilaginous envelopes or sheaths were reported as separate entities, and not as a part of Microcystis colonies. The colonial sheaths may contain a few single Microcystis cells and reach significant numbers (thousands) during a cyanobacterial bloom. We also found that non-identifiable colonial small clusters of Microcystis cells are an important stage in the complex mosaic of a Microcystis bloom and are associated with the development of colonial forms. Our findings were validated by the principal component analysis coupled with the constructed associative matrices. We hypothesize that colonial sheaths may be crucial at Microcystis spp. dispersal and represent one of the stages of colonies development.

ecology↗

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↗

bioRxiv2019

Probing complexity of microalgae mixtures with novel spectral flow cytometry approach and \"virtual filtering\"

Fluorescence methods are widely applied for the study of the marine and freshwater phytoplankton communities. However, identification of different microalgae populations by autofluorescent pigments remains a challenge because of the very strong signal from chlorophyll. Addressing the issue we developed a novel approach using the flexibility of spectral flow cytometry analysis (SFC) and generated a matrix of virtual filters (VF) capable to of differentiating non-chlorophyll parts of the spectrum. Using this matrix spectral emission regions of algae species were analyzed, and five major algal taxa were discriminated. These results were further applied for tracing particular microalgae taxa in the complex mixtures of laboratory and environmental algal populations. An integrated analysis of single algal events combined with unique spectral emission fingerprints and light scattering parameters of microalgae can be further used to differentiate major microalgal taxa. Our results demonstrate that spectral flow cytometer (SFC-VF) and virtual filtering approach can provide a quantitative assessing of heterogenous phytoplankton communities at single cell level spectra and be helpful in the monitoring of phytoplankton blooms.\n\nO_LIThe research was partly presented during AQUAFLUO II Colloquium 2017, Sydney, Australia and ISAC Congress, Boston 2017\nC_LI

ecology↗