From acid seeps and deep-sea thermal vents to glacial ice and hypersaline lakes, extreme environments contain relatively simplified communities consisting of extremophiles that have evolved to survive and thrive under adverse abiotic conditions. In more neutral environments, microorganisms use dormancy as a common life history strategy to weather temporal fluctuations of resources or stresses until more 'optimal' conditions are present. It is unclear if dormancy is an essential survival mechanism for microorganisms in extreme environments; however, recent studies suggest that extreme environments may create stable conditions for extremophiles to the extent that dormancy is of less ecological importance. Using lake salinity levels as measurements of "extreme," we evaluated the dormancy of bacterial and archaeal phyla and lake chemistry in five hypersaline and five freshwater lakes across the western United States. Dormancy was calculated using targeted metagenomics to analyze 16S rDNA and rRNA tag sequences. It was hypothesized that bacteria and archaea in hypersaline lake communities would exhibit lower levels dormancy than bacterial and archaeal communities in geologically similar freshwater lake controls. It was also hypothesized that microbial dormancy would decrease as the dominant extreme environmental variable increased in the lakes. As hypothesized, overall dormancy decreased at least 2-fold in hypersaline compared to freshwater lakes for both bacteria and archaea. Of the predominant phyla and subclasses, Firmicutes, Bacteroidetes, and Gammaproteobacteria each demonstrated at least a seven-fold decrease in dormancy in hypersaline lakes compared to freshwater lakes. Specifically, species within the genus Clostridium were responsible for 85% of the dormancy observed in the phylum Firmicutes. Also as hypothesized, microbial dormancy decreased as salinity increased in the lakes. Lower dormancy in hypersaline lakes correlated with increasing salinity while lower dormancy in freshwater lakes correlated with increasing total phosphorus levels. These results suggest that dormancy is a less common life history strategy for microorganisms in extreme environments; it is proposed that this is due to the relatively stable environment in hypersaline lakes and the reduced number of available microbial niches. These results also suggest that the dominant extreme stress (i.e., salinity) may override other driving factors in an environment to ultimately determine microbial community composition, diversity and richness.

Multiple mechanisms control bacterial community structure but two in particular, the "legacy" of past environmental conditions, and the "priming" of bacteria to respond to seasonal or reoccurring fluctuations in resources, have the potential to determine both bacterial communities, as well as, temporal shifts in active bacterial taxa. To begin to evaluate the legacy effects of resources on microbial communities, we added four limiting resources annually (i.e., water only; C-mannitol + water; N-NH4NO3 + water; and C, N + water) and measured shifts in bacterial community composition after seven years in a cold desert ecosystem in the McMurdo Dry Valleys, Antarctica. Further, to investigate the ecological significance of priming, we conducted a series of stable isotope probing experiments (i.e., 18O-DNA SIP with 18O-labeled water, 13C-DNA SIP with 13C-labeled mannitol, 15N-DNA with 15N- NH4NO3, and a combined C and N SIP) and characterized the responding (i.e., isotopically labeled) and seed bank (i.e., unlabeled) bacterial communities. We performed each of the SIPs in soil microcosms corresponding to a single resource manipulation (e.g., 13C-labeled mannitol in C addition soils). We hypothesized that all long-term additions of nutrients and water will lead to a distinct bacterial community—a legacy effect due to the nutrient and water impoverished state of Antarctica soils. We also hypothesized that the stronger the legacy effects demonstrated by a specific community the more adapted or primed bacterial species will be to take advantage of the resource and respond. As hypothesized, resource additions created distinct bacterial legacy but to different degrees among the treatments. The extent of the resource legacy effects was greatest in the CN, intermediate in water and N, and lowest in C communities relative to the control communities, suggesting that C induced changes in communities were intensified by tandem N additions and that water alone created a more distinct legacy than water and C additions combined. Contrary to our hypothesis, the stronger the legacy effects, the less adapted or primed the community was to take advantage of resource additions. For example, the CN treatment that induced the greatest effect on bacterial communities had the lowest number of species (20.9%) in common between the responding and seed bank communities. This inverse relationship may be due to only two species (i.e., Arthrobacter, Actinobacteria and Massilia, Betaproteobacteria) really being primed to take advantage of CN and these species constituting over 75% of the seed bank community. Water, N, and C additions had similar levels of priming with 38.4%, 41.4%, and 36.3% of the responding species being present in the seed bank community, respectively. But of these three treatments, only the priming with water resulted in a unique responding community, suggesting that water, a universal bacterial resource, was enough to prime bacteria. Furthermore, water generates the most diverse responding community of all the resources with stemming from all of the fourteen dominant phyla. We did find patterns of ecological coherence among the responders, especially in the major responders (i.e., responders that increased in relative recovery by at least ten-fold). These responders were predominantly found in only three phyla (i.e., Actinobacteria, Bacteriodetes, and Gammaproteobacteria) regardless of resource addition. Alternatively minor responders (i.e., responders that increased in relative recovery at least two-fold) were contained in fourteen different phyla with specific taxa stimulated by CN (i.e., Betaproteobacteria) and N and water (i.e., Deltaproteobacteria). Further, resource additions elicited responses from 37% of bacterial species with species specializing on a specific resource (e.g., Chloroflexi) or being a generalist (e.g., Planctomycetes and Gammaproteobacteria). Our results offer the first direct links between legacy and priming effects on bacterial community composition and demonstrate that these mechanisms are not always complimentary leading to the formation of similar communities but may both be essential to maintain the high levels of bacterial diversity. Further, all resources produced elicited responders that were either specialists of generalists demonstrating that even bacteria in the extreme environment of Antarctica respond to pulses of resources.

The development of Massively Parallel Sequencing (MPS) has enabled more accurate and less time-consuming DNA sequencing. Although MPS technologies are theoretically applicable to all samples and species, the majority of studies on microorganisms have been conducted on those able to be isolated and cultivated in laboratories. In the field of metagenomics, DNA from uncultivated environmental samples is analyzed. Whole genome sequencing of such complex samples poses difficult computational challenges due to the characteristics of metagenomic data, where one major challenge lies in determining the true origin of high similarity reads. In addition, the short-range information acquired from MPS reveals little about how reads from DNA sequencing fit together. Consequently, producing genome drafts from reads generated by MPS remains difficult. Here, the linked-read sequencing technology DB-Seq has been applied to bacterial samples in order to assess its potential in metagenomics. Specifically, its performance in retaining long-range information in de novo whole genome assembly has been tested. The results obtained in this initial study show great potential of DB-Seq in genome assembly, with significantly more contiguous results than conventional methods generate. / Utvecklingen av Massiv Parallel Sekvensering (MPS) har möjliggjort mer korrekt och mindre tidskrävande DNA sekvensering. Trots att MPS teoretiskt sett kan appliceras på alla provtyper och arter, har majoriteten av de studier som utförts på mikroorganismer varit fokuserade på de som kan isoleras och odlas i laboratorium. Inom ämnet metagenomik analyseras DNA från orörda miljöprover. Helgenomssekvensering av sådana prover ger upphov till komplicerade utmaningar för data-analys, där ett av de största problemen är att bestämma ursprunget av snarlika sekvenseringsresultat. Ytterligare komplikationer uppstår på grund av den data som erhålls från MPS, då denna ej ger information om hur sekvenseringsdata bör placeras i förhållande till varandra. Följdaktligen är det svårt att producera hopsatta genom utifrån MPS-data. I detta projekt har "linked-read"-sekvenseringsteknologin DB-Seq applicerats på bakterieprover för att undersöka metodens potential i metagenomik. Specifikt har metodens förmåga att bibehålla information om ursprungspositionen av sekvenseringsdata testats i de novo sammansättning av genom. De erhållna resultaten i denna förstagångsstudie tyder på stor potential för DB-Seq i genomsammansättning, med signifikant mer sammanhängande resultatsekvenser än vad konventionella metoder uppvisar.

Nausea and vomiting are among the most common symptoms of early pregnancy. Its most extreme form Hyperemesis gravidarum often requires hospitalization and has been linked as a risk factor of perinatal depression. The emetic reflex is to a large extent triggered in the intestinal epithelium by the enterochromaffin cells, however the interplay between gut microbiome and pregnancy nausea is yet unclear. The aim of this study is to investigate the variation in gut microbiota diversity on second-trimester pregnant women with different levels of nausea, and to ascertain potential key species involved in that variation. Using shotgun sequencing to capture bacterial diversity from 1078 fecal samples, we found a reduction on species richness on women with strong nausea. There are measurable differences in the gut microbiota community composition based on the strength of nausea although depression seemed to be even more relevant to explain those differences. Our results provide evidence for the association of nausea and perinatal depression, but further studies are needed to elucidate the mechanisms underpinning the gut-brain axis cross-talk role in nausea and perinatal depression. No evidence of variation in species evenness or differential abundance of species were found. Finally, random forests results point at Lactococcus lactis as potentially displaying a key role determining the intensity of the nausea, although better models are needed to infer clear assumptions.

京都大学 / 新制・課程博士 / 博士(農学) / 甲第24677号 / 農博第2560号 / 新制||農||1100(附属図書館) / 学位論文||R5||N5458(農学部図書室) / 京都大学大学院農学研究科応用生物科学専攻 / (主査)教授 吉田 天士, 教授 澤山 茂樹, 准教授 神川 龍馬 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

Rapidly accumulating genomic data as a result of high-throughput sequencing has necessitated development of efficient computational methods to decode the biological information underlying these data. DNA composition varies across structurally or functionally different regions of a genome as well as those of distinct evolutionary origins. We adapted an integrative framework that combines a top-down, recursive segmentation algorithm with a bottom-up, agglomerative clustering algorithm to decipher compositionally distinct regions in genomes. The recursive segmentation procedure entails fragmenting a genome into compositionally distinct segments within a statistical hypothesis testing framework. This is followed by an agglomerative clustering procedure to group compositionally similar segments within the same framework. One of our main objectives was to decipher distinctive evolutionary patterns in sex chromosomes via unraveling the underlying compositional heterogeneity. Application of this approach to the human X-chromosome provided novel insights into the stratification of the X chromosome as a consequence of punctuated recombination suppressions between the X and Y from the distal long arm to the distal short arm. Novel "evolutionary strata" were identified particularly in the X conserved region (XCR) that is not amenable to the X-Y comparative analysis due to massive loss of the Y gametologs following recombination cessation. Our compositional based approach could circumvent the limitations of the current methods that depend on X-Y (or Z-W for ZW sex determination system) comparisons by deciphering the stratification even if only the sequence of sex chromosome in the homogametic sex (i.e. X or Z chromosome) is available. These studies were extended to the plant sex chromosomes which are known to have a number of evolutionary strata that formed at the initial stage of their evolution, presenting an opportunity to examine the onset of stratum formation on the sex chromosomes. Further applications included detection of horizontally acquired DNAs in extremophilic eukaryote, Galdieria sulphuraria, which encode variety of potentially adaptive functions, and in the taxonomic profiling of metagenomic sequences. Finally, we discussed how the Markovian segmentation and clustering method can be made more sensitive and robust for further applications in biological and biomedical sciences in future.

Archaeological dental calculus represents a depositional environment that entraps oral microbes, and debris of dietary, environmental, and cultural material that entered the mouth throughout the host’s life. Hence, they represent valuable archives of information about the host’s lifestyle, health, and environment. The aim of this study was to identify if the farming transition and its’ associated change in diet composition, may have influenced species composition in the oral cavity. To shed some light into the evolution of ancient oral microbiomes from Africa, 3 novel Iron Age dental calculus metagenomes together with a comparative dataset of 18 archaeological dental calculus metagenomes from North African Upper Palaeolithic, Later Stone Age, Iron Age, and 18th-19th century populations where analysed. Shotgun sequencing data was used to reconstruct 21 oral metagenomes from the past 15,000 years. This study found an oral microbiome that has been maintained from the Upper Palaeolithic (North Africa) to the 19th Century. However, closer examination to the relative abundance of three keystone species of the subgingival plaque, portray a chronological evolution that reflects that of its host during the major dietary and cultural transition that occurred during the farming revolution in the Iron Age.

Antibiotic resistance (AR) is a pervasive crisis that is intricately woven into social and environmental systems. Its escalation is fueled by factors such overuse, poverty, climate change, and the heightened interconnectedness characteristic of our era of globalization. In this dissertation, the impact of antibiotic usage is addressed from the perspective of wastewater-based surveillance (WBS) at the wastewater treatment plant (WWTP) and microbial ecology. Antibiotic usage and contamination was found to influence the prevalence of antibiotic resistance genes (ARGs) and resistant bacteria in both lab-scale and full-scale wastewater treatment settings. Through application of novel bioinformatic approaches developed herein, metagenomics revealed associations between sewage-associated microbes and community antibiotic use that were in part mediated by microbial ecological processes and horizontal gene transfer (HGT). In sum, this dissertation increases the arsenal of bioinformatic tools for AR surveillance in wastewater environments and advances knowledge with respect to the contribution of antibiotic use to the spread of antibiotic resistance at the community-scale. Three studies served to evaluate and/or develop bioinformatic resources for molecular characterization of AR in wastewater. Hybrid assembly combining emerging long read DNA sequencing and short read sequencing was evaluated and found to improve accuracy relative to assembly of long or short reads alone. A novel database of mobile genetic element (MGE) marker genes, mobileOG-db, was compiled in order to address short-comings with pre-existing resources. A pipeline for detecting HGT in metagenomes, Kairos, was created in order to facilitate the detection of HGT in metagenome assemblies which greatly amplified coverage of ARGs. In Chapter 5, a lab-scale study of WWTP bioreactors revealed that elevated antibiotic contamination was correlated with increased prevalence of corresponding ARGs. In addition, multiple in situ HGT events of ARGs encoding resistance to the elevated antibiotics were predicted, including one HGT event likely mediated by a novel bacteriophage. In Chapter 6, influent and effluent from a full-scale municipal WWTP were collected twice-weekly for one year and subjected to deep shotgun metagenomic sequencing. In parallel, collaboration with clinicians enabled statistical modeling of antibiotic usage and resistance, revealing associations between antibiotic prescriptions patterns in the region and resistance at the WWTP. Finally, Chapter 7 details bioinformatic recovery of diverse extended spectrum beta-lactamase gene recovery from the influent and effluent metagenomes, shedding light on the dynamics of circulating resistance genes. In sum, this dissertation identifies bioinformatic evidence for the selection of AR in wastewater environments as a result of antibiotic use in the community and advances hypotheses for explaining the mechanisms of the observed phenomena. / Doctor of Philosophy / Antibiotics are key lifesaving drugs that have dramatically improved life expectancy throughout the 20th and 21st centuries. However, there has been an increased incidence of resistance among many important bacterial pathogens in recent decades. The more antibiotics are used, the more chance that resistant bacteria can evolve, survive, and spread. Outpatient care accounts for the vast majority of therapeutic antibiotic use, with more than 200 million prescriptions written for antibiotics in 2021 in the United States. While performing a vital function in combatting disease, oral antibiotics can inadvertently harm the resident microbes of the intestinal tract (i.e., the gut microbiome) by decreasing the diversity of the microbes present and increasing the number of resistant bacteria. At a community level, antibiotic usage also has the potential to induce increased prevalence of antibiotics and antibiotic resistant bacteria in the environment as well, primarily via human excreta (urine and feces). Wastewater represents a key interface between human-derived contaminants and the environment. In regions with centralized wastewater management, antibiotics- and resistant bacteria-containing excreta are typically transported via sewage conveyance systems to a wastewater treatment plant (WWTP). At the WWTP, diverse microbes interact with and degrade various organic contaminants in a series of processes combining physical, chemical, and biological treatments. Due to the intermingling of environmental microbes, antibiotics, and antibiotic resistant bacteria, wastewater is increasingly being recognized as an important venue for antibiotic resistance surveillance and for potential interventions. Awareness of wastewater-based surveillance and epidemiology has surged as a result of the COVID-19 pandemic and such efforts are enshrined in the National COVID-19 Preparedness Plan. However, such a task is fundamentally more challenging for antibiotic resistance than for SARS-CoV-2, as it comprises multiple bacterial strains, antibiotic resistance genes, and resistance mechanisms. In this respect, DNA sequencing of wastewater, i.e., "metagenomics," holds promise as a broad monitoring tool with an unprecedented degree of biological granularity. In this dissertation, we address the impact of antibiotic usage at the WWTP from the perspective of wastewater-based surveillance. We evaluate antibiotic usage at the community-scale as a selective force among bacteria inhabiting WWTPs and identify microbial interactions that influence the escape of resistant bacteria in the effluent. A field-study of wastewater entering the WWTP and cleaned effluent water discharged by the WWTP revealed certain antibiotics and corresponding forms of antibiotic resistance were particularly prone to proliferation in the WWTP. Novel bioinformatic tools were developed and applied to the study of wastewater to reveal these associations. In sum, this dissertation advances knowledge of wastewater as both a mediator of environmental health and as a reflection of community-health in the form of antibiotic resistance.

Metagenomics is a cultivation-independent approach for obtaining the genomic composition of microbial communities. Microbial communities are ubiquitous in nature. Microbes which are associated with the human body play important roles in human health and disease. These roles span from protecting us against infections from other bacteria, to being the causes of these diseases. A deeper understanding of these communities and how they function inside our bodies allows for advancements in treatments and preventions for these diseases. Recent developments in metagenomics have been driven by the emergence of Next-Generation Sequencing technologies and Third-Generation Sequencing technologies that have enabled cost-effective DNA sequencing and the generation of large volumes of genomic data. These technologies have allowed for the introduction of hybrid DNA assembly techniques to recover the genomes of the constituent microbes. While Next-Generation Sequencing technologies use paired-end sequencing reads from DNA fragments into short reads and have a relatively lower error rate, Third-Generation Sequencing technologies use much longer DNA fragments to generate longer reads, bringing contigs together for larger scaffolds with a higher error rate. Hybrid assemblers leverage both short and long read sequencing technologies and can be a critical step in the advancements of metagenomics, combining these technologies to allow for longer assemblies of DNA with lower error rates. We evaluate the strengths and weaknesses of the hybrid assembly framework using several state-of-the-art assemblers and simulated human microbiome datasets. Our work provides insights into metagenomic assembly and genome recovery, an important step towards a deeper understanding of the microbial communities that influence our well-being.

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