Kamil Khanipov

Slim-Filter: an interactive windows-based application for illumina genome analyzer data assessment and manipulation

BackgroundThe emergence of Next Generation Sequencing technologies has made it possible for individual investigators to generate gigabases of sequencing data per week. Effective analysis and manipulation of these data is limited due to large file sizes, so even simple tasks such as data filtration and quality assessment have to be performed in several steps. This requires (potentially problematic) interaction between the investigator and a bioinformatics/computational service provider. Furthermore, such services are often performed using specialized computational facilities.ResultsWe present a Windows-based application, Slim-Filter designed to interactively examine the statistical properties of sequencing reads produced by Illumina Genome Analyzer and to perform a broad spectrum of data manipulation tasks including: filtration of low quality and low complexity reads; filtration of reads containing undesired subsequences (such as parts of adapters and PCR primers used during the sample and sequencing libraries preparation steps); excluding duplicated reads (while keeping each read’s copy number information in a specialized data format); and sorting reads by copy numbers allowing for easy access and manual editing of the resulting files. Slim-Filter is organized as a sequence of windows summarizing the statistical properties of the reads. Each data manipulation step has roll-back abilities, allowing for return to previous steps of the data analysis process. Slim-Filter is written in C++ and is compatible with fasta, fastq, and specialized AS file formats presented in this manuscript. Setup files and a user’s manual are available for download at the supplementary web site (https://www.bioinfo.uh.edu/Slim_Filter/).ConclusionThe presented Windows-based application has been developed with the goal of providing individual investigators with integrated sequencing reads analysis, curation, and manipulation capabilities.

Small Regulatory RNAs of Rickettsia conorii

Small regulatory RNAs comprise critically important modulators of gene expression in bacteria, yet very little is known about their prevalence and functions in Rickettsia species. R. conorii, the causative agent of Mediterranean spotted fever, is a tick-borne pathogen that primarily infects microvascular endothelium in humans. We have determined the transcriptional landscape of R. conorii during infection of Human Microvascular Endothelial Cells (HMECs) by strand-specific RNA sequencing to identify 4 riboswitches, 13 trans-acting (intergenic), and 22 cis-acting (antisense) small RNAs (termed ‘Rc_sR’s). Independent expression of four novel trans-acting sRNAs (Rc_sR31, Rc_sR33, Rc_sR35, and Rc_sR42) and known bacterial sRNAs (6S, RNaseP_bact_a, ffs, and α-tmRNA) was next confirmed by Northern hybridization. Comparative analysis during infection of HMECs vis-à-vis tick AAE2 cells revealed significantly higher expression of Rc_sR35 and Rc_sR42 in HMECs, whereas Rc_sR31 and Rc_sR33 were expressed at similar levels in both cell types. We further predicted a total of 502 genes involved in all important biological processes as potential targets of Rc_sRs and validated the interaction of Rc_sR42 with cydA (cytochrome d ubiquinol oxidase subunit I). Our findings constitute the first evidence of the existence of post-transcriptional riboregulatory mechanisms in R. conorii and interactions between a novel Rc_sR and its target mRNA.

Identification and Characterization of Novel Small RNAs in Rickettsia prowazekii

Emerging evidence implicates a critically important role for bacterial small RNAs (sRNAs) as post-transcriptional regulators of physiology, metabolism, stress/adaptive responses, and virulence, but the roles of sRNAs in pathogenic Rickettsia species remain poorly understood. Here, we report on the identification of both novel and well-known bacterial sRNAs in Rickettsia prowazekii, known to cause epidemic typhus in humans. RNA sequencing of human microvascular endothelial cells (HMECs), the preferred targets during human rickettsioses, infected with R. prowazekii revealed the presence of 35 trans-acting and 23 cis-acting sRNAs, respectively. Of these, expression of two trans-acting (Rp_sR17 and Rp_sR60) and one cis-acting (Rp_sR47) novel sRNAs and four well-characterized bacterial sRNAs (RNaseP_bact_a, α-tmRNA, 4.5S RNA, 6S RNA) was further confirmed by Northern blot or RT-PCR analyses. The transcriptional start sites of five novel rickettsial sRNAs and 6S RNA were next determined using 5′ RLM-RACE yielding evidence for their independent biogenesis in R. prowazekii. Finally, computational approaches were employed to determine the secondary structures and potential mRNA targets of novel sRNAs. Together, these results establish the presence and expression of sRNAs in R. prowazekii during host cell infection and suggest potential functional roles for these important post-transcriptional regulators in rickettsial biology and pathogenesis.

Nasopharyngeal microbiota in infants and changes during viral upper respiratory tract infection and acute otitis media

Background Interferences between pathogenic bacteria and specific commensals are known. We determined the interactions between nasopharyngeal microbial pathogens and commensals during viral upper respiratory tract infection (URI) and acute otitis media (AOM) in infants. Methods We analyzed 971 specimens collected monthly and during URI and AOM episodes from 139 infants. The 16S rRNA V4 gene regions were sequenced on the Illumina MiSeq platform. Results Among the high abundant genus-level nasopharyngeal microbiota were Moraxella, Haemophilus, and Streptococcus (3 otopathogen genera), Corynebacterium, Dolosigranulum, Staphylococcus, Acinetobacter, Pseudomonas, and Bifidobacterium. Bacterial diversity was lower in culture-positive samples for Streptococcus pneumoniae, and Haemophilus influenzae, compared to cultured-negative samples. URI frequencies were positively associated with increasing trend in otopathogen colonization. AOM frequencies were associated with decreasing trend in Micrococcus colonization. During URI and AOM, there were increases in abundance of otopathogen genera and decreases in Pseudomonas, Myroides, Yersinia, and Sphingomonas. Otopathogen abundance was increased during symptomatic viral infection, but not during asymptomatic infection. The risk for AOM complicating URI was reduced by increased abundance of Staphylococcus and Sphingobium. Conclusion Otopathogen genera played the key roles in URI and AOM occurrences. Staphylococcus counteracts otopathogens thus Staphylococcal colonization may be beneficial, rather than harmful. While Sphingobium may play a role in preventing AOM complicating URI, the commonly used probiotic Bifidobacterium did not play a significant role during URI or AOM. The role of less common commensals in counteracting the deleterious effects of otopathogens requires further studies.

Transcriptional profiling of Rickettsia prowazekii coding and non-coding transcripts during in vitro host-pathogen and vector-pathogen interactions

Natural pathogen transmission of Rickettsia prowazekii, the etiologic agent of epidemic typhus, to humans is associated with arthropods, including human body lice, ticks, and ectoparasites of eastern flying squirrel. Recently, we have documented the presence of small RNAs in Rickettsia species and expression of R. prowazekii sRNAs during infection of cultured human microvascular endothelial cells (HMECs), which represent the primary target cells during human infections. Bacterial noncoding transcripts are now well established as critical post-transcriptional regulators of virulence and adaptation mechanisms in varying host environments. Despite their importance, little is known about the expression profile and regulatory activities of R. prowazekii sRNAs (Rp_sRs) in different host cells encountered as part of the natural life-cycle. To investigate the sRNA expression profile of R. prowazekii during infection of arthropod host cells, we employed an approach combining in vitro infection, bioinformatics, RNA sequencing, and PCR-based quantitation. Global analysis of R. prowazekii transcriptome by strand-specific RNA sequencing enabled us to identify 67 cis-acting (antisense) and 26 trans-acting (intergenic) Rp_sRs expressed during the infection of Amblyomma americanum (AAE2) cells. Comparative evaluation of expression during R. prowazekii infection of HMECs and AAE2 cells by quantitative RT-PCR demonstrated significantly higher expression of four selected Rp_sRs in tick AAE2 cells. Examination of the coding transcriptome revealed differential up-regulation of >150 rickettsial genes in either HMECs or AAE2 cells and yielded evidence for host cell-dependent utilization of alternative transcription start sites by 18 rickettsial genes. Our results thus suggest noticeable differences in the expression of both Rp_sRs as well as the coding transcriptome and the exploitation of multiple transcription initiation sites for select genes during the infection of human endothelium and tick vector cells as the host and yield new insights into rickettsial virulence and transmission mechanisms.

Assessing the utility of metabarcoding for diet analyses of the omnivorous wild pig (Sus scrofa)

Abstract Wild pigs (Sus scrofa) are an invasive species descended from both domestic swine and Eurasian wild boar that was introduced to North America during the early 1500s. Wild pigs have since become the most abundant free‐ranging exotic ungulate in the United States. Large and ever‐increasing populations of wild pigs negatively impact agriculture, sport hunting, and native ecosystems with costs estimated to exceed

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

1.5 billion/year within the United States. Wild pigs are recognized as generalist feeders, able to exploit a broad array of locally available food resources, yet their feeding behaviors remain poorly understood as partially digested material is often unidentifiable through traditional stomach content analyses. To overcome the limitation of stomach content analyses, we developed a DNA sequencing‐based protocol to describe the plant and animal diet composition of wild pigs. Additionally, we developed and evaluated blocking primers to reduce the amplification and sequencing of host DNA, thus providing greater returns of sequences from diet items. We demonstrate that the use of blocking primers produces significantly more sequencing reads per sample from diet items, which increases the robustness of ascertaining animal diet composition with molecular tools. Further, we show that the overall plant and animal diet composition is significantly different between the three areas sampled, demonstrating this approach is suitable for describing differences in diet composition among the locations.

Expression Profiling of Long Noncoding RNA Splice Variants in Human Microvascular Endothelial Cells: Lipopolysaccharide Effects In Vitro

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.

The ability of human nuclear DNA to cause false positive low-abundance heteroplasmy calls varies across the mitochondrial genome

Endothelial cell interactions with lipopolysaccharide (LPS) involve both activating and repressing signals resulting in pronounced alterations in their transcriptome and proteome. Noncoding RNAs are now appreciated as posttranscriptional and translational regulators of cellular signaling and responses, but their expression status and roles during endothelial interactions with LPS are not well understood. We report on the expression profile of long noncoding (lnc) RNAs of human microvascular endothelial cells in response to LPS. We have identified a total of 10,781 and 8310 lncRNA transcripts displaying either positive or negative regulation of expression, respectively, at 3 and 24 h posttreatment. A majority of LPS-induced lncRNAs are multiexonic and distributed across the genome as evidenced by their presence on all chromosomes. Present among these are a total of 44 lncRNAs with known regulatory functions, of which 41 multiexonic lncRNAs have multiple splice variants. We have further validated splice variant-specific expression of EGO (NONHSAT087634) and HOTAIRM1 (NONHSAT119666) at 3 h and significant upregulation of lnc-IL7R at 24 h. This study illustrates the genome-wide regulation of endothelial lncRNA splice variants in response to LPS and provides a foundation for further investigations of differentially expressed lncRNA transcripts in endothelial responses to LPS and pathophysiology of sepsis/septic shock.

CoCo: An application to store High-Throughput Sequencing data in compact text and binary file formats

BackgroundLow-abundance mutations in mitochondrial populations (mutations with minor allele frequency ≤ 1%), are associated with cancer, aging, and neurodegenerative disorders. While recent progress in high-throughput sequencing technology has significantly improved the heteroplasmy identification process, the ability of this technology to detect low-abundance mutations can be affected by the presence of similar sequences originating from nuclear DNA (nDNA). To determine to what extent nDNA can cause false positive low-abundance heteroplasmy calls, we have identified mitochondrial locations of all subsequences that are common or similar (one mismatch allowed) between nDNA and mitochondrial DNA (mtDNA).ResultsPerformed analysis revealed up to a 25-fold variation in the lengths of longest common and longest similar (one mismatch allowed) subsequences across the mitochondrial genome. The size of the longest subsequences shared between nDNA and mtDNA in several regions of the mitochondrial genome were found to be as low as 11 bases, which not only allows using these regions to design new, very specific PCR primers, but also supports the hypothesis of the non-random introduction of mtDNA into the human nuclear DNA.ConclusionAnalysis of the mitochondrial locations of the subsequences shared between nDNA and mtDNA suggested that even very short (36 bases) single-end sequencing reads can be used to identify low-abundance variation in 20.4% of the mitochondrial genome. For longer (76 and 150 bases) reads, the proportion of the mitochondrial genome where nDNA presence will not interfere found to be 44.5 and 67.9%, when low-abundance mutations at 100% of locations can be identified using 417 bases long single reads. This observation suggests that the analysis of low-abundance variations in mitochondria population can be extended to a variety of large data collections such as NCBI Sequence Read Archive, European Nucleotide Archive, The Cancer Genome Atlas, and International Cancer Genome Consortium.