Biology subjects

Golovko, G.

Publications and source records attributed to Golovko, G..

5 recordsLinked to original sources

bioRxiv2018

Novel Wolbachia strains in Anopheles malaria vectors from Sub-Saharan Africa

Anopheles (An.) mosquitoes contain bacteria that can influence Plasmodium parasites. Wolbachia, a common insect endosymbiont, has historically been considered absent from Anopheles but has recently been found in An. gambiae populations. Here, we assessed a range of Anopheles species from five malaria-endemic countries for Wolbachia and Plasmodium infection. Strikingly, we found Wolbachia infections in An. coluzzii, An. gambiae s.s, An. arabiensis, An. moucheti and An. species A increasing the number of Anopheles species known to be naturally infected by this endosymbiont. Molecular analysis suggests the presence of phylogenetically diverse novel strains, while qPCR and 16S rRNA sequencing indicates that Wolbachia is the dominant member of the microbiota in An. moucheti and An. species A. We found no evidence of Wolbachia/Asaia co-infections, and presence of these endosymbionts did not have significant effects on malaria prevalence. We discuss the importance of novel Wolbachia strains in Anopheles and potential implications for disease control.

microbiology↗

bioRxiv2018

Microbiome interaction networks and community structure from lab-reared and field-collected Aedes aegypti, Aedes albopictus, and Culex quinquefasciatus mosquito vectors.

Microbial interactions are an underappreciated force in shaping insect microbiome communities. Although pairwise patterns of symbiont interactions have been identified, we have a poor understanding regarding the scale and the nature of co-occurrence and co-exclusion interactions within the microbiome. To characterize these patterns in mosquitoes, we sequenced the bacterial microbiome of Aedes aegypti, Ae. albopictus, and Culex quinquefasciatus caught in the field or reared in the laboratory and used these data to generate interaction networks. For collections, we used traps that attracted host-seeking or ovipositing female mosquitoes to determine how physiological state affects the microbiome under field conditions. Interestingly, we saw few differences in species richness or microbiome community structure in mosquitoes caught in either trap. Co-occurrence and co-exclusion analysis identified 116 pairwise interactions substantially increasing the list of bacterial interactions observed in mosquitoes. Networks generated from the microbiome of Ae. aegypti often included highly interconnected hub bacteria. There were several instances where co-occurring bacteria co-excluded a third taxa, suggesting the existence of tripartite relationships. Several associations were observed in multiple species or in field and laboratory-reared mosquitoes indicating these associations are robust and not influenced by environmental or host factors. To demonstrate that microbial interactions can influence colonization of the host, we administered symbionts to Ae. aegypti larvae that either possessed or lacked their resident microbiota. We found that the presence of resident microbiota can inhibit colonization of particular bacterial taxa. Our results highlight that microbial interactions in mosquitoes are complex and influence microbiome composition.

microbiology↗

bioRxiv2018

Using High Throughput DNA Sequencing to Evaluate the Accuracy of Serial Dilution Based Tests of Microbial Activities in Oil Pipelines

Microbial activities have detrimental effects on industrial infrastructure. If not controlled, microbial presence can result in corrosion, biofilm formation, and product degradation. Serial dilution tests are routinely used for evaluating presence and abundance of microorganisms by diluting samples and culturing microbes in specific media designed to support microorganisms with particular properties, such as sulfate reduction.\n\nA high-throughput sequencing approach was used to evaluate changes in microbial composition during four standard serial dilution tests. Analysis of 159 isolates revealed significant differences in the microbial compositions of sequential serial dilution titers and identified several cases where: (a) bacteria known to have a detrimental metabolic function (such as acid production) were lost in the serial dilution medium designed to test for this function; (b) bacteria virtually absent in the original sample became dominant in the serial dilution medium. These observations raise concerns regarding the accuracy and overall usefulness of serial dilution tests.

microbiology↗

bioRxiv2018

Detection of Multidimensional Co-Exclusion Patterns in Microbial Communities

MotivationIdentification of complex relationships among members of microbial communities is key to understand and control the microbiota. Co-exclusion is arguably one of the most important patterns reflecting microorganisms intolerance to each others presence. Knowing these relations opens an opportunity to manipulate microbiotas, personalize anti-microbial and probiotic treatments as well as guide microbiota transplantation. The co-exclusion pattern however, cannot be appropriately described by a linear function nor its strength be estimated using covariance or (negative) Pearson and Spearman correlation coefficients. This manuscript proposes a way to quantify the strength and evaluate the statistical significance of co-exclusion patterns between two, three or more variables describing a microbiota and allows one to extend analysis beyond microorganism abundance by including other microbiome associated measurements such as, pH, temperature etc., as well as estimate the expected numbers of false positive co-exclusion patterns in a co-exclusion network.\n\nResultsThe implemented computational pipeline (CoEx) tested against 2,380 microbial profiles (samples) from The Human Microbiome Project resulted in body-site specific pairwise co-exclusion patterns.\n\nAvailabilityC++ source code for calculation of the score and p-value for 2, 3, and 4 dimensional co-exclusion patterns as well as source code and executable files for the CoEx pipeline are available at https://scsb.utmb.edu/labgroups/fofanov/co-exclusion_in_microbial_communities.asp\n\nContactlealbayr@utmb.edu\n\nSupplementary informationSupplementary data are available at biorxiv online.

genomics↗

bioRxiv2018

Broom: Application for non-redundant storage of High Throughput Sequencing data

MotivationThe data generation capabilities of High Throughput Sequencing (HTS) instruments have exponentially increased over the last few years, while the cost of sequencing has dramatically decreased allowing this technology to become widely used in biomedical studies. For small labs and individual researchers, however, storage and transfer of large amounts of HTS data present a significant challenge. The recent trends in increased sequencing quality and genome coverage can be used to reconsider HTS data storage strategies.\n\nResultsWe present Broom, a stand-alone application designed to select and store only high-quality sequencing reads at extremely high compression rates. Written in C++, the application accepts single and paired-end reads in FASTQ and FASTA formats and decompresses data in FASTA format.\n\nAvailabilityC++ code available at https://scsb.utmb.edu/labgroups/fofanov/broom.asp\n\nContactlealbayr@utmb.edu

bioinformatics↗