Repertoire of Intensive Care Unit Pneumonia Microbiota

Despite the considerable number of studies reported to date, the causative agents of pneumonia are not completely identified. We comprehensively applied modern and traditional laboratory diagnostic techniques to identify microbiota in patients who were admitted to or developed pneumonia in intensive care units (ICUs). During a three-year period, we tested the bronchoalveolar lavage (BAL) of patients with ventilator-associated pneumonia, community-acquired pneumonia, non-ventilator ICU pneumonia and aspiration pneumonia, and compared the results with those from patients without pneumonia (controls). Samples were tested by amplification of 16S rDNA, 18S rDNA genes followed by cloning and sequencing and by PCR to target specific pathogens. We also included culture, amoeba co-culture, detection of antibodies to selected agents and urinary antigen tests. Based on molecular testing, we identified a wide repertoire of 160 bacterial species of which 73 have not been previously reported in pneumonia. Moreover, we found 37 putative new bacterial phylotypes with a 16S rDNA gene divergence ≥98% from known phylotypes. We also identified 24 fungal species of which 6 have not been previously reported in pneumonia and 7 viruses. Patients can present up to 16 different microorganisms in a single BAL (mean ± SD; 3.77±2.93). Some pathogens considered to be typical for ICU pneumonia such as Pseudomonas aeruginosa and Streptococcus species can be detected as commonly in controls as in pneumonia patients which strikingly highlights the existence of a core pulmonary microbiota. Differences in the microbiota of different forms of pneumonia were documented

The influence of HIV-1 genomic target region selection and sequence length on the accuracy of inferred phylogenies and clustering outcomes.

Masters Degree. University of KwaZulu-Natal, Durban.To improve the methodology of HIV-1 cluster analysis, we addressed how analysis of HIV-1 clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering, tree certainty, subtype diversity ratio (SDR), subtype diversity variance (SDV) and Shimodaira-Hasegawa (SH)-like support values were compared between 2881 HIV-1 full genome sequences and sub-genomic regions of which 2567 were retrieved from the LANL HIV Database and 314 were sequenced from blood samples from a cohort in KwaZulu-Natal. Sliding window analysis was based on 99 windows of 1000 bp, 45 windows of 2000 bp and 27 windows of 3000 bp. Clusters were enumerated for each window sequence length, and the optimal sequence length for cluster identification was probed. Potential associations between the extent of HIV clustering and sequence length were also evaluated. The phylogeny based on the full-genome sequences showed the best tree accuracy; it ranked highest with regards to both tree certainty and SH-like support. Product 4, a region associated with env, had the best tree accuracy among the sub-genomic regions. Among the HIV-1 structural genes, env had the best tree certainty, SH-like support, SDR score and the best SDV score overall. The hierarchy of cluster phylotype enumeration mirrored the tree accuracy analysis, with the full genome phylogeny showing the highest extent of clustering, and the product 4 region being second best. Among the structural genes, the highest number of phylotypes was enumerated from the pol phylogeny, followed by env. The extent of HIV-1 clustering was slightly higher for sliding windows of 3 000 bp than 2000 bp and 1000 bp, thus 3000 bp was found to be the optimal length for phylogenetic cluster analysis. We found a moderate association between the length of sequences used and proportion of HIV sequences in clusters; the influence of viral sequence length may have been diminished by the substantial number of taxa. Full-genome sequences could provide the most informative HIV cluster analysis. Selected sub-genomic regions with the best combination of high extent of HIV clustering and high tree accuracy, such as env, could also be considered as a second choice

Variant antigen repertoires in Trypanosoma congolense populations and experimental infections can be profiled from deep sequence data using universal protein motifs

African trypanosomes are vector-borne hemoparasites of humans and animals. In the mammal, parasites evade the immune response through antigenic variation. Periodic switching of the Variant Surface Glycoprotein (VSG) coat covering their cell surface allows sequential expansion of serologically distinct parasite clones. Trypanosome genomes contain many hundreds of VSG genes, subject to rapid changes in nucleotide sequence, copy number and chromosomal position. Thus, analysing, or even quantifying, VSG diversity over space and time presents an enormous challenge to conventional techniques. Indeed, previous population genomic studies have overlooked this vital aspect of pathogen biology for lack of analytical tools. Here we present a method for analysing population-scale VSG diversity in Trypanosoma congolense from deep sequencing data. Previously, we suggested that T. congolense VSG segregate into defined 'phylotypes' that do not recombine. In our dataset comprising 41 T. congolense genome sequences from across Africa, these phylotypes are universal and exhaustive. Screening sequence contigs with diagnostic protein motifs accurately quantifies relative phylotype frequencies, providing a metric of VSG diversity, called the 'Variant Antigen Profile'. We applied our metric to VSG expression in the tsetse fly, showing that certain, rare VSG phylotypes may be preferentially expressed in infective, metacyclic-stage parasites. Hence, variant antigen profiling accurately and rapidly determines VSG gene and transcript repertoire from sequence data, without need for manual curation or highly contiguous sequences. It offers a tractable approach to measuring VSG diversity across strains and during infections, which is imperative to understanding the host-parasite interaction at population and individual scales. [Abstract copyright: Published by Cold Spring Harbor Laboratory Press.

Sulestiku bakterikoosluste pesitsusaegne varieeruvus kahel vabaltelaval värvuliseliigil

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Mikrorganismid mängivad loomade elukäigu kujundamisel olulist rolli ja hiljuti on välja tuldud ideega, et sulgi lagundavad bakterid võivad mõjutada lindude sigimispingutuse ja sulestiku puhastamise vahel olevat lõivsuhet, mõjutades seeläbi ka pesitsusedukust. Selleks, et planeerida lindude edukuse ja nende sulestikku asustavate bakterite vaheliste põhjuslike seoste kindlakstegemiseks katseid, tuleb esmalt õppida paremini mõistma sulestiku bakterikoosluste looduslikku varieeruvust. Töös uuriti rasvatihase (Parus major) ja must-kärbsenäpi (Ficedula hypoleuca) populatsioone, kirjeldamaks sulgi asustavaid bakterikooslusi ja uurida nende seoseid keskkonna ja elukäigu parameetritega. Bakterite arvukuse ja mitmekesisuse määramiseks kasutati vastavalt läbivoolu tsütomeetriat ja ribosomaalse geenidevahelise speisserjärjestuse analüüsi (RISA). Bakterite arvukus ja mitmekesisus leiti sõltuvat linnuliigist ja pesitsusbiotoobist. Bakterite arvukus oli oluliselt erinev paariliste, kehaosade ja aastate vahel, olles samaaegselt ühe isendi (ja pesitsuspaari) piires, võrrelduna teiste isenditega (ja pesitsuspaaridega), siiski tugevas seoses. Mõlemal linnuliigil leiti emastel bakterite arvukus kõrgem olevat kui isastel, mis koos varasemate andmetega viitab selle mustri üldkehtivusele. Pesitsushooaja jooksul bakterite arvukus muutus tugevasti: järsk tõus pesaehituse ajal, sellele järgnev langus esimese kurna ajal ning uus tõus enne teise pesakonna lennuvõimestumist. Bakterite arvukus oli seotud emaste kehamassi ja pesitsusedukusega (lennuvõimestunud poegade hulk), aga mitmekesisus oli negatiivses seoses hoopiski sulestiku eredusega (mida samuti peetakse isendi kvaliteedi näitajaks). Veelgi enam, bakterite arvukuse muutus pesitsushooajal oli negatiivses seoses sulestiku ereduse muutusega samal perioodil. Seega, käesolev uurimus kinnitab, et pesitsevate lindude sulgedel elavad bakterikooslused on mõjutatud nii lindude elukäigust kui ka ökoloogilistest parameetritest ja on seoses kehakonditsiooniga. Pesaehituseaegne kiire bakterite arvukuse kasv viitab ühele võimalikule pesaehituse hinnale. Siiski, kõigi leitud seoste põhjuslikkus vajab veel eksperimentaalset testimist.Microorganisms have been shown to play an important role in shaping the life- histories of animals, and it has recently been suggested that feather-degrading bacteria influence the trade-off between parental effort and self-preening behavior in birds, therefore affecting breeding success. However, to design suitable experiments to examine causal relationships between plumage bacteria and the fitness of host birds, natural variation in plumage bacterial communities needs to be better understood. Wild breeding populations of great tits (Parus major) and Pied Flycatchers (Ficedula hypoleuca) were studied in purpose to explore bacterial assemblages inhabiting the feathers and to investigate associations with ecological and life-history parameters. The density and species richness of bacterial assemblages were studied using flow cytometry and ribosomal intergenic spacer analysis (RISA) respectively. Bacterial load and assemblage richness were found to associate with species and habitat. Bacterial load was significantly different between pairmates, body parts of the same bird and different years, same time there were strong intra-individual (and intrapair) correlations of mentioned factors. In both species bacterial load was higher in females than in males, which along with earlier studies, indicates the generality of this sex pattern. There were significant seasonal changes in bacterial abundance on feathers: increase during nest-building, decline between the nest-building period and fledging of the first brood and increase again before fledging of the second brood. Bacterial abundance was associated with female body mass and breeding success (number of fledglings), but feather-degrading bacterial phylotypic richness was negatively related to female feather chroma (which is also considered to show individual quality). Also, seasonal change in the density of attached bacteria associating with individual birds was negatively associated with change in chroma over the same period. Thus, this study revealed that bacterial assemblages on the feathers of breeding birds are affected both by life history and ecological factors and are related to body condition. Rapid change of bacterial abundance during nest-building may provide one potential cost of nest-building for individual birds. However, the causality of these associations remains to be tested experimentally

The Role of Phylogenetics as a Tool to Predict the Spread of Resistance

Drug resistance mutations emerge in genetic sequences of HIV through drug-selective pressure. Drug resistance can be transmitted. In this review we discuss phylogenetic methods used to study the emergence of drug resistance and the spread of resistant viruses

Expansion of Microbial Virology by Impetus of the Reduction of Viral Dark Matter

Modern metagenomic methods have rapidly accelerated the rate of viral discovery. Currently, to discover a novel virus, deep sequencing reads must align to a known reference virus. While alignment is effective at identifying closely related viruses, highly divergent viruses can often share no discernable sequence alignment with known viruses. Therefore, the accurate classification of viral dark matter – metagenomic sequences that originate from viruses but do not align to any reference virus sequences – is one of the major obstacles in not only discovering novel viruses, but also by extension, comprehensively defining the virome. As viral dark matter results fundamentally from a failure to align sequence reads, two major contributors to viral dark matter include 1) the lack of diversity in specific viral families and 2) the reliance on alignment as a metric to define viral taxonomy. In this dissertation, I address each of these issues. These projects resulted in a massive expansion in understanding of microbial virus diversity, which led me to further interrogate the biology of microbial viruses. Specifically, I attempted to identify novel antiviral mechanisms against RNA bacteriophages and possibly identify a novel family of RNA bacteriophages. First, I addressed the underrepresentation of viral sequences in databases by identifying a specific underrepresented class of virus, bacteriophages with RNA genomes, and systematically discovered highly divergent novel RNA bacteriophages in previously sequenced data. I identified 161 partial genome sequences from at least 122 RNA bacteriophage phylotypes that are highly divergent from each other and from previously described RNA bacteriophages. These partial genome sequences displayed multiple novel genome organizations previously unknown for RNA bacteriophages, and in aggregate, encoded 91 open reading frames (ORFs) that did not align to any known protein; sequences related to these ORFs would be described as viral dark matter in absentia of this systematic discovery effort. This new level RNA bacteriophage diversity suggested that RNA bacteriophages might be major predators of bacteria in the environment. In turn, this would suggest that there might be active resistance mechanisms in bacteria that specifically antagonize RNA bacteriophages; as of now however, there are no active mechanisms known in bacteria that can antagonize RNA bacteriophages. Therefore, one goal was to identify bacterial genes that can restrict RNA bacteriophage infection. I performed a functional metagenomic screen to identify RNA phage resistance genes. From this, I identified four genes that conferred resistance to the RNA phages, Qβ and MS2 but not the RNA phage C1. Additionally, this expansion of RNA bacteriophage diversity suggests that there might be new families of RNA bacteriophages that are unrelated to the previously discovered RNA bacteriophages. One candidate eukaryotic viral family that might in fact be RNA bacteriophages are Picobirnaviridae. Picobirnaviruses are bisegmented RNA viruses that are highly prevalent in stool. By analyzing previously sequenced datasets, I discovered multiple new picobirnavirus segments. From analyzing the upstream regions of the ORFs on these segments, I found that almost all of the ORFs are preceded by a bacterial ribosomal binding sequence. This conservation of bacterial ribosomal binding sequences suggests that these viruses might infect bacteria. I then unsuccessfully tried to show that Human Picobirnavirus can replicate in bacterial cells. Second, I addressed the reliance on alignment based algorithms by developing a novel alignment-independent algorithm to identify viral sequences. This algorithm, DiscoVir, is a support vector machine (SVM) model that relies on nucleotide k-mer frequencies to discriminate sequences of novel, highly disparate eukaryotic viruses from prokaryotic and fungal sequences. I validated in silico that DiscoVir can identify viruses from novel viral taxa and that it outperforms BLASTx for almost all viral families. When applied to an authentic metagenomic dataset, DiscoVir identified two additional contigs that corresponded to two undetected segments of a novel bunya-like virus. By selectively culturing fungi from this serum sample, I identified an isolate of Penicillium atramentosum that contained all three viral RNA segments, thus suggesting that this fungal isolate was in fact the host of this novel virus. I sequenced the whole genome of this novel virus and demonstrated that the terminal nucleotide sequences were conserved between the three segments, and these sequences were consistent with the termini of bunyaviruses in the genera Phlebovirus and Tenuivirus. Thus, application of DiscoVir played a critical role in the identification of the first segmented negative stranded RNA virus infection of a fungus. Taken together, I have contributed to the systematic reduction of viral dark matter using two different approaches, both of which enable future researchers to identify a much more diverse repertoire of viruses than previously possible. This increased ability to identify highly divergent viruses will better enable the metagenomics community to accurately identify the role of viruses in larger biological processes, including but not limited to, human disease