abstract / Biological Sciences / Doctoral / Doctor of Philosophy

Giant pandas are unique animals because of their digestive system is similar to carnivores but they have in fact adapted to a plant diet with bamboo as their main food source. According to fossils records, giant pandas were omnivorous approximately 7 million years ago, becoming almost vegetarian after 4.6 to 5 million years of evolution. However, their genome and anatomical structure do not favor bamboo digestion. For more than a decade, researchers have been questioning the underlying mechanism of their ability to digest bamboo. In 2010, the genome of giant panda was completed, which confirmed that their genome had no gene encoding for cellulolytic enzymes. Thus, the gut microbiota of giant panda, which has been hypothesized to play a key role in bamboo digestion, has garnered unprecedented attention. Researchers are also interested in the giant panda’s gut microbes due to their potential application in biomass conversion. In Chapters 2 and 3 of this thesis, the microbial catalog of the giant panda’s gut microbiota was characterized, showing possible age-related microbial dysbiosis. Moreover, the microbiota, both bacterial and fungal was highly individualized because very few operational taxonomic units were shared among the four pandas in this study. Novel homoacetogens were also identified in the giant panda using functional gene clone-library sequencing. Using metagenomic sequencing, I uncovered the first evidence of human and animal related viruses in the giant panda’s gut. In addition to the community structure, I also determined the metabolic pathways of the microbiome. From KEGG annotation, a metabolic pathway for both cellulose and hemicellulose metabolism was identified. Comparative metagenomic analysis indicated that the giant panda’s gut microbiome was taxonomically and functionally distinct from those in mammals. In Chapters 4 and 5, a total of 97 species of bacteria were isolated and identified using biochemical assays. Four of these bacteria showed powerful cellulolytic and hemicellulolytic activities on solid media. The gram-positive bacteria (HKUOP_BS) and the gram-negative bacteria (HKUOP_A14) were found to be rod shaped, facultative anaerobes that had the ability to powerfully hydrolyze both cellulose and hemicellulose using intracellular and extracellular enzymes respectively. In Chapter 6, I determined the complete genome of a cellulolytic bacterium, Klebsiella oxytoca HKUOPL1, from giant panda and further described the annotated virulence, drug resistant, functional and potential horizontal transferring genes. The phylogenomic tree indicated that K. oxytoca HKUOPL1 closely resembled the K. oxytoca KCTC 1686 strain commonly used in 2,3-butanediol production. In captive giant pandas, a mucous excretion episode usually occurs with mild to severe colic. To understand the host-microbial interactions during this episode, bacterial communities were compared between mucous excreta and normal feces. The shifts in community abundance (especially flooding of Clostridia) may be associated with the mucous excretion episode. This study provides a better understanding of the microbial community structure and function in the giant panda’s gut. / published_or_final_version / Biological Sciences / Doctoral / Doctor of Philosophy

To investigate the diversities and abundances of nitrifiers and to apply the highthroughput sequencing technologies to analyze the overall microbial community structures and functions in the wastewater treatment bioreactors were the major objectives of this study. Specifically, this study was conducted: (1) to investigate the diversities and abundances of AOA, AOB and NOB in bioreactors, (2) to explore the bacterial communities in bioreactors using 454 pyrosequencing, and (3) to analyze the metagenomes of activated sludge using Illumina sequencing. A lab-scale nitrification bioreactor was operated for 342 days under low DO (0.15~0.5 mg/L) and high nitrogen loading (0.26~0.52 kg-N/(m3d)). T-RFLP and cloning analysis showed there were only one dominant AOA, AOB and NOB species in the bioreactor, respectively. The amoA gene of the dominant AOA had a similarity of 89.3% with the isolated AOA species Nitrosopumilus maritimus SCM1. The AOB species detected in the bioreactor belonged to Nitrosomonas genus. The abundance of AOB was more than 40 times larger than that of AOA. The percentage of NOB in total bacteria increased from not detectable to 30% when DO changed from 0.15 to 0.5 mg/L. Compared with traditional methods, pyrosequencing analysis of the bacteria in this bioreactor provided unprecedented information. 494 bacterial OTUs was obtained at 3% distance cutoff. Furthermore, 454 pyrosequencing was applied to investigate the bacterial communities of activated sludge samples from 14 WWTPs of Asia (mainland China, Hong Kong, and Singapore) and North America (Canada and the United States). The results revealed huge amounts of OTUs in activated sludge, i.e. 1183~3567 OTUs in one sludge sample at 3% distance cutoff. Clear geographical differences among these samples were observed. The AOB amoA genes in different WWTPs were found quite diverse while the 16S rRNA genes were relatively conserved. To explore microbial community structures and functions in the abovementioned labscale bioreactor and a full-scale bioreactor, over six gigabases of metagenomic sequence data and 150,000 paired-end reads of PCR amplicons were generated from the activated sludge in the two bioreactors on Illumina HiSeq2000 platform. Three kinds of sequences (16S rRNA amplicons, 16S rRNA gene tags and predicted genes) were used to conduct taxonomic assignment and their applicabilities and reliabilities were compared. Specially, based on 16S rRNA and amoA gene sequences, AOB were found more abundant than AOA in the two bioreactors. Furthermore, the analysis of the metabolic profiles and pathways indicated that the overall pathways in the two bioreactors were quite similar. However, the abundances of some specific genes in the two bioreactors were different. In addition, 454 pyrosequencing was also used to detect potentially pathogenic bacteria in environmental samples. It was found most abundant potentially pathogenic bacteria in the WWTPs were affiliated with Aeromonas and Clostridium. Aeromonas veronii, Aeromonas hydrophila and Clostridium perfringens were species most similar to the potentially pathogenic bacteria found in this study. Overall, the percentage of the sequences closely related to known pathogenic bacteria sequences was about 0.16% of the total sequences. Additionally, a Java application (BAND) was developed for graphical visualization of microbial abundance data. / published_or_final_version / Civil Engineering / Doctoral / Doctor of Philosophy

Thesis (Ph.D.)--Syracuse University, 2008. / "Publication number: AAT 3323087."

Baculoviruses have been used as biocontrol agents to control insect pests in agriculture since the 1970s. Out of the fifteen virus families known to infect insects, baculoviruses offer the greatest potential as insect biopesticides, due to their high host specificity which makes them extremely safe to humans, other vertebrates, plants and non-target microorganisms. They comprise of two genera: nucleopolyhedroviruses (NPVs) and granuloviruses (GVs). The South African isolate of Cryptophlebia leucotreta granulovirus (CrleGV-SA) which is infectious for the false codling moth (FCM), Thaumatotibia leucotreta, (Meyrick) (Lepidoptera: Tortricidae), has been successfully developed into two commercial biopesticides; Cryptogran® and Cryptex®, for the control of FCM in citrus crops. The current method of enumeration used for CrleGV-SA virus particles in routine experiments during the production of the GV as biopesticides, is dark field microscopy. However, due to the small size of GVs (300-500 nm in length), the technique is not easy to perform on these viruses, and no systemic comparison has been made of potential alternative methods. Therefore, the main objective of this study was to develop a quantitative enumeration method for CrleGV-SA occlusion bodies (OBs) which is accurate, reliable, and feasible, and compare the developed methods of enumeration to the current method. Purified and semi-purified CrleGV-SA viral stocks were prepared for enumeration studies using spectrophotometry, dark field microscopy, scanning electron microscopy (SEM) and real time qPCR. Spectrophotometry was found to be an unreliable method for enumeration of GVs in the production, standardisation, and quality control of biopesticides. Dark field microscopy and SEM were found to be accurate, and statistically comparable (p = 0.064) enumeration techniques. qPCR is currently being optimised for the enumeration of GVs. This technique was demonstrated to generate accurate standard curves for absolute quantification of virus particles for pure and semi-pure virus preparations. qPCR offers the greatest potential as an accurate enumeration method because it is not affected by contamination with non-biological contaminating debris, nor by other biological material due to the specificity of PCR primers. Further work is required to fully develop qPCR as an enumeration method for GVs. However, dark field microscopy has been successfully validated as an enumeration method. SEM, which has a high resolution compared to light microscopy, has an added advantage over dark field microscopy, which is to distinguish virus particles in semi-pure viral stock preparations during counting. Therefore, SEM currently provides the most unambiguous and feasible enumeration method for GVs in both purified and semi-purified virus samples.

This study evaluated the stability of oral bacteria in healthy subjects and documented community shifts in smokers and oral/periodontal disease by employing PCR-RFLP, DGGE and sequence analysis of the 16S rDNA gene from metagenomes and plate-wash (cultured) bacteria of oral wash from 15 participants,. A stable core of bacterial DNA fingerprint was detected within and between subjects and did not change over time when analyzed in smokers and healthy non-smokers. Signature bands in smokers, non-smokers and periodontal disease subjects were evident suggesting the presence of potential indicators of health and poor oral health. Taxon diversity was higher in smokers including members of the genera Rothia, Synechococcus, Neisseria, Thiomargarita and Pyrobaculum but highest in periodontal disease. The two techniques successfully aligned the subjects within appropriate categories (based on their oral microbial genetic patterns)confirming their diagnostic suitability. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

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No. of bitstreams: 2 dissertacao_frederico_schmitt_kremer.pdf: 1606431 bytes, checksum: 192db9fb559b24dfd0b3038659fdd5b7 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-02-17 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / O advento do sequenciamento de DNA de nova geração (NGS) reduziu significativamente o custo dos projetos de sequenciamento de genomas. Quanto mais fácil é de obter novos dados genômicos, mais acuradas deve ser a etapa de anotação, de forma a se reduzir a perda de informações relevantes e efetuar o acúmulo de erros que possam afetar a acurácia das análises posteriores. No caso dos genomas bacterianos, um grande número de programas para anotação já foi desenvolvido, entretanto, muitos destes softwares não incorporaram etapas para otimizar os seus resultados, como filtragem de proteínas falso-positivas/spurious e a anotação mais completa de RNA não-codificantes. O presente trabalho descreve o desenvolvimento do Genix, uma nova pipeline automatizada que combina a funcionalidade de diferentes softwares, incluindo Prodigal, tRNAscan-SE, RNAmmer, Aragorn, INFERNAL, NCBI-BLAST+, CD-HIT, Rfam e Uniprot, com a intenção de aumentar a afetividade dos resultados de anotação. Para avaliar a acurácia da presente ferramenta, foram usados como modelo de estudo os genomas de referência de Escherichia coli K-12, Leptospira interrogans cepa Fiocruz L1-130, Listeria monocytogenese EGD-e e Mycobacterium tuberculosis H37Rv. Os resultados obtidos pelo Genix foram comparados às anotações originais e as obtidas pelas ferramentas de anotação RAST e BASys, considerando genes novos, faltantes e exclusivos, informações de anotação funcional e predições de ORFs spurious. De forma a se quantificar o grau de acurácia, uma nova métrica, denominada discrepância de anotação foi também proposta. Na análise comparativa o Genix apresentou para todos os genomas o menor valor de discrepância, variando entre 0,96 e 5,71%, sendo o maior valor observado no genoma de L. interrogans, para o qual RAST e BASys apresentaram valores superiores a 14,0%. Além disso, foram identificadas proteínas spurious nas anotações geradas pelos demais programas, e, em menor número, nas anotações de referência, indicando que a utilização do Antifam permite um melhor controle do número de genes falso positivos. A partir dos testes realizados, foi possível demonstrar que o Genix é capaz de gerar anotação com boa acurácia (baixo discrepância), menor perda de genes relevantes (funcionais) e menor número de genes falso positivos. / The advent of next-generation sequencing (NGS) significantly reduced the cost of genome sequencing projects. The easier it is to generate genomic data, the more accurate the annotation steps must to be to avoid both the loss of information and the accumulation of erroneous features that may affect the accuracy of further analysis. In the case of bacteria genomes, a range of web annotation software has been developed; however, many applications have not incorporated the steps required to improve the output (eg: false-positive/spurious ORF filtering and a more complete non-coding RNA annotation). The present work describes the implementation of Genix, a new bacteria genome annotation pipeline that combines the functionality of the programs Prodigal, tRNAscan-SE, RNAmmer, Aragorn, INFERNAL, NCBI-BLAST+, CD-HIT, Rfam and UniProt, with the intention of increasing the effectiveness of the annotation results. To evaluate the accuracy of Genix, we used as models of study the reference genomes of Escherichia coli K-12, Leptospira interrogans strain Fiocruz L1-130, Listeria monocytogenes EGD-e and Mycobacterium tuberculosis H37Rv. the results obtained by Genix were compared to the original annotation and to those from the annotation pipelines RAST and BASys considering new, missing and exclusive genes, functional annotation information and the prediction of spurious ORFs. To quantify the annotation accuracy, a new metric, called “annotation discrepancy” was developed. In a comparative analysis, Genix showed the smallest discrepancy for the four genomes, ranging for 0.96 to 5.71%, the highest discrepancy was bserved in the L. interrogans genome, for which RAST and BASys resulted in discrepancies greater than 14.0%. Additionally, several spurious proteins were identified in the annotations generated by RAST and BASys, and, in smaller number, in the reference annotations, indicating that the use of the Antifam database allows a better control of the number of false-positive genes. Based on the evaluations, it was possible to show that Genix is able to generate annotations with good accuracy (low discrepancy), low omission of relevant (functional) genes and a small number of false-positive genes.

Understanding microbial evolution lies at the heart of microbiology and environmental sciences. Numerous studies have been dedicated to elucidating the underlying mechanisms that create microbial genetic diversity and adaptation. However, due to technical limitations such as the high level of uncultured cells in almost every natural habitat, most of current knowledge is primarily based on axenic cultures grown under laboratory conditions, which typically do not simulate well the natural environment. How well the knowledge from isolates translates to in-situ processes and natural microbial communities remains essentially speculative. The recent development of culture-independent genomic techniques (aka metagenomics) provides possibilities to bypass some of these limitations and provide new insights into microbial evolution in-situ. To date, most of metagenomic studies have been focused on a few reduced-diversity model communities, e.g., acid mine drainage. Highly complex communities such as those of soil and sediment habitats remain comparatively less understood. Furthermore, a great power of metagenomics, which has not been fully capitalized yet, is the ability to follow the evolution of natural microbial communities over time and environmental perturbations, i.e., times-series metagenomics. Although the recent developments in DNA sequencing technologies have enabled (inexpensive) time-series studies, the bioinformatics approaches to analyze the resulting data have clearly fallen behind. Taken together, to scale up metagenomics for complex community studies, three major challenges remain: 1) the difficulty to process and analyze massive short read sequencing data, often at the terabyte level; 2) the difficulty to effectively assemble genomes from complex metagenomes; and 3) the lack of methods for tracking genotypes and mutational events such as horizontal gene transfer (HGT) through time. Therefore, developing efficient bioinformatics approaches to address these challenges represents an important and timely issue. This thesis aimed to develop novel bioinformatics pipelines and algorithms for high performance computing, and, subsequently, apply these tools to natural microbial communities to generate quantitative insights into the relative importance of the molecular mechanisms creating or maintaining microbial diversity. The tools are not specific to a particular habitat or group of organisms and thus, can be broadly used to advance our understanding of microbial evolution in different settings. In particular, the comparative whole-genome analysis of 24 Escherichia isolates form various habitats, including human and non-human associated habitats such as freshwater ecosystems and beaches, showed that organisms with more similar ecologies tend to exchange more genes, which has important implications for the prokaryotic species concept. To more directly test these findings from isolates and quantify the patterns of genetic exchange among co-occurring populations, three years of time-series metagenomics data from planktonic samples from Lake Lanier (Atlanta, GA) were analyzed. For this, it was first important to develop bioinformatics algorithms to robustly assemble population genomes from complex community metagenomes, identify the phylogenetic affiliation of assembled genome and contig sequences, and detect horizontal gene transfer among these sequences. Using these novel algorithms, in situ bacterial lineage evolution was quantitatively assessed, especially with respect to whether or not ecologically distinct lineages evolve according to the recently proposed fragmented speciation model (Retchless and Lawrence, Science 2008). Evidence in support of this model was rarely observed. Instead, it appeared that rampant HGT disseminated ecologically important genes within the population, maintaining intra-population diversity. By expanding the previous approaches to include methods to assess differential gene abundance and selection pressure between samples, it was possible to quantify how soil microbial communities respond to a decade of warming by 2 0C, which simulated the predicted effects of climate change. It was found that the heated communities showed significant shifts in composition and predicted metabolism, reflecting the release of additional soil carbon compared to the unheated (control) communities, and these shifts were community-wide as opposed to being attributable to a few taxa. These findings indicated that the microbial communities of temperate grassland soils play important roles in mediating the feedback responses to climate change. Collectively, the findings presented here advance our understanding of the modes and tempo of microbial community adaptation to environmental perturbations and have important implications for better modeling the microbial diversity on the planet. The bioinformatics algorithms and approaches developed as part of this thesis are expected to facilitate future genomic and metagenomic studies across the fields of microbiology, ecology, evolution and engineering.

Bacteria evolve during the colonization of human hosts, yet little is known about the selective pressures and evolutionary forces that shape this evolution. Illumination of these processes may inspire new therapeutic directions for combating bacterial infections and promoting healthy bacteria-host interactions. The advent of high-throughput sequencing has enabled the identification of mutations that occur within the human host, and various tools from computational and evolutionary biology can aid in creating biological understanding from these mutations. Chapter 1 describes recent progress in understanding within-patient bacterial adaption, focusing on insights made from genomic studies.

Most plant pathogens are specialists where only few plant species are susceptible, while all other plants are resistant. Unraveling the mechanisms behind this can thus provide valuable information for breeding or engineering crops with durable disease resistance. A group of Pseudomonas syringae strains with different host ranges while still closely related were thus chosen for comparative study. We confirmed their close phylogenetic relationship. We found evidence supporting that these strains recombined during evolution. The Arabidopsis thaliana and tomato pathogen P. syringae pv. tomato (Pto) DC3000 was found to be an atypical tomato strain, distinct from the typical Pto strains commonly isolated in the field that do not cause disease in A. thaliana, such as Pto T1. Comparing A. thaliana defense responses to DC3000 and T1, we found that T1 is eliciting stronger responses than DC3000. T1 is likely lacking Type III effector genes necessary to suppress plant defense. To test this, we sequenced the genomes of strains that cause and do not cause disease in A. thaliana. Comparative genomics revealed candidate effector genes responsible for this host range difference. Effector genes conserved in strains pathogenic in A. thaliana were expressed in T1 to test whether they would allow T1 to growth better in A. thaliana. Surprisingly, most of them reduced T1 growth. One of the effectors, HopM1, was of particular interest because it is disrupted in typical Pto strains. Although HopM1 has known virulence function in A. thaliana, HopM1 reduced T1 growth in both A. thaliana and tomato. HopM1 also increased the number of bacterial specks but reduced their average size in tomato. Our data suggest that HopM1 can trigger defenses in these plants. Additionally, transgenic detritivore Pseudomonas fluorescens that can secrete HopM1 shows dramatically increased growth in planta. The importance of genetic background of the pathogen for the functions of individual effectors is discussed. T1 cannot be manipulated to become an A. thaliana pathogen by deleting or adding individual genes. We now have a list of genes that can be studied in the future for the molecular basis of host range determination. / Ph. D.