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2000-2019

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Browsing 2000-2019 by Author "Abdo, Zaid, committee member"

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    Epidemiological investigation of antimicrobial resistance in beef production using metagenomic sequencing
    (Colorado State University. Libraries, 2019) Doster, Enrique, author; Hoover, Edward A., advisor; Morley, Paul S., advisor; Belk, Keith E., committee member; Abdo, Zaid, committee member; Gow, Sheryl P., committee member
    Globally, the emergence of antimicrobial resistance (AMR) resulting in treatment failure is recognized as a growing public health threat. Antimicrobial use practices used in beef production are thought to be a direct driver of increasing antimicrobial resistance in pathogens and the environment, in part due to the higher volumes of antimicrobial drug necessary to treat cattle weighing 10 times more than an average person. This has led policy makers and public health organizations to promote "judicious use" or outright ban of antimicrobial drugs in livestock production. Use of antimicrobials is unavoidable for the treatment of disease and we must therefore learn how we can best adjust our AMD use to reduce selection of AMR pathogens. However, outside of important indicator organisms and pathogens, little is known about how different antimicrobial drug use practices affect communities of microorganisms, or microbiomes, and the AMR gene determinants, or resistome, shared between pathogen and non-pathogens alike. With advances in high-throughput sequencing (HTS), we can perform culture-independent studies and gain a better understanding of how antimicrobial drug use practices in livestock production affect AMR epidemiology. This dissertation consists of five studies that employ HTS to characterize the microbiome and resistome of samples with differing AMD exposure along the beef production line. Projects begin with a look into the short-term effects on the microbiome and resistome of feedlot cattle following treatment with a macrolide drug, tulathromycin, in the manuscript "Investigating Effects of Tulathromycin Metaphylaxis on the Fecal Resistome and Microbiome of Commercial Feedlot Cattle Early in the Feeding Period". Fecal samples collected in this project also were processed with aerobic culture, polymerase chain reaction (PCR), and lateral flow immunoassay for identification of Salmonella enterica and the comparison of these results are presented in "A Cautionary Report for Pathogen Identification Using Shotgun Metagenomics; a Comparison to Aerobic Culture and Polymerase Chain Reaction for Salmonella enterica Identification". Samples collected as part of a longitudinal study in feedlot cattle were analyzed to characterize the associations between AMD use and AMR in two bacterial species. These archived samples are leveraged for a broader understanding of AMR dynamics by adding a community-level perspective to results from aerobic culture. Results in individual cattle are presented in "Antimicrobial Drug Use in Beef Feedlots; Effects on the Microbiome and Resistome Dynamics in Individual Cattle" and results at the pen-level in "Metagenomic Investigation of the Effects of Antimicrobial Drug Use Practices on the Microbiome and Resistome of Beef Feedlot Cattle". Finally, in "Metagenomic Characterization of the Microbiome and Resistome in Retail Ground Beef" we examined the end of the beef production line by comparing the microbiome and resistome of retail ground beef products from either conventional production systems or those labeled as "raised with antibiotics" (RWA). The five studies presented in this dissertation each contribute to the collective understanding of how AMD use in livestock production system can affect the ecology of AMR in microbial communities. These projects are useful first steps in learning to manage AMR in beef production systems; encompassing a targeted look at the use of one type of AMD, characterizing the resistome dynamics in individual cattle and pens over time in a feedlot, a comparison of the resistome in ground beef products, and many other aspects of AMR epidemiology. The final study, describing limits to incorporating HTS for pathogen identification, serves as a cautionary reminder that with new technologies come new challenges and that research must keep pace.
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    Read alignment using deep neural networks
    (Colorado State University. Libraries, 2019) Shrestha, Akash, author; Chitsaz, Hamidreza, advisor; Ben-Hur, Asa, committee member; Abdo, Zaid, committee member
    Read alignment is the process of mapping short DNA sequences into the reference genome. With the advent of consecutively evolving "next generation" sequencing technologies, the need for sequence alignment tools appeared. Many scientific communities and the companies marketing the sequencing technologies developed a whole spectrum of read aligners/mappers for different error profiles and read length characteristics. Among the most recent successfully marketed sequencing technologies are Oxford Nanopore and PacBio SMRT sequencing, which are considered top players because of their extremely long reads and low cost. However, the reads may contain error up to 20% that are not generally uniformly distributed. To deal with that level of error rate and read length, proximity preserving hashing techniques, such as Minhash and Minimizers, were utilized to quickly map a read to the target region of the reference sequence. Subsequently, a variant of global or local alignment dynamic programming is then used to give the final alignment. In this research work, we train a Deep Neural Network (DNN) to yield a hashing scheme for the highly erroneous long reads, which is deemed superior to Minhash for mapping the reads. We implemented that idea to build a read alignment tool: DNNAligner. We evaluated the performance of our aligner against the popular read aligners in the bioinformatics community currently — minimap2, bwa-mem and graphmap. Our results show that the performance of DNNAligner is comparable to other tools without any code optimization or integration of other advanced features. Moreover, DNN exhibits superior performance in comparison with Minhashon neighborhood classification.
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    The epidemiology and ecology of Escherichia coli O157 on U.S. dairies
    (Colorado State University. Libraries, 2018) Stenkamp-Strahm, Chloe Marie, author; Reynolds, Stephen, advisor; McConnel, Craig, advisor; Magzamen, Sheryl, committee member; Lombard, Jason, committee member; Abdo, Zaid, committee member
    Escherichia coli O157 (O157) is a bacterium that causes human foodborne disease outbreaks worldwide. Beef and dairy cattle are reservoirs for O157, as they harbor the bacteria in their lower gastrointestinal (GI) tracts and shed it in feces without clinical illness. Humans become infected with O157 after contacting cows or manure, or ingesting the bacteria on dairy, meat or produce products. Dairy cattle are a central part of the U.S food supply, providing milk for a multitude of dairy products, and 15-20% of the beef produced. Transmission of O157 from dairy cattle to humans is reduced by techniques that limit bacterial survival after food is harvested (i.e. post-harvest). However, O157 outbreaks occur after post-harvest dairy pasteurization and slaughter laws are applied across the U.S food chain. Due to these outbreaks, an emphasis has been placed on developing methods that reduce O157 presence prior to harvest (i.e pre-harvest) at the dairy farm. An understanding of dairy cow O157 prevalence and magnitude of shedding, and animal-level correlates for shedding, may aid in the development of pre-harvest O157 strategies. We hypothesized that life history features (parity, history of disease, others) would be associated with O157 shedding by adult cows on Colorado dairies, and that shedding in early lactation would be correlated with shedding detected during the pre-weaning period of these dams' calves. Although overall prevalence was low (3.0%) and only one individual shed O157 at a high magnitude (>103 CFU/g feces), a higher number of adult cows shed O157 between June and October. Dams were at increased risk of shedding if they were a lower parity, earlier days in milk, or had a history of antibiotic use. Calf shedding was not detected on the Colorado dairies studied; no correlation between dam and calf O157 shedding was present. We hypothesized that the lack of calf shedding was due to the sampling time-frame, calf management, and the geographic region of study. Using fecal samples collected by the National Animal Health Monitoring System (NAHMS) from dairy calves across the U.S, we estimated the prevalence of O157 shedding and managerial, environmental, and calf-level variables associated with pathogen presence. U.S calf shedding of O157 was low (2.5 %) and not influenced by geographic region. Calves were at increased risk to shed if they received colostrum from their own dam, which suggests that increased time spent with the dam is associated with shedding. Results indicated that the passive transfer status of calves also influenced shedding, but was affected by the temperature and humidity index (THI) calves were exposed to during pre-weaning. Calves experiencing thermoneutral or heat-stress THIs were more likely to shed O157 if they had poor or moderate passive transfer. Calves were unlikely to shed if they had excellent passive transfer, regardless of THI. Herds of cattle likely have uniform levels of O157 exposure, but only some individuals shed the bacteria. We hypothesized that the GI microbial community influenced which cows become colonized with O157 post-ingestion. After measuring microbial communities in naturally infected cows on Colorado dairies, lower microbial richness (i.e. total number of unique species) was associated with intermittent or multi-day shedding of O157. The species Bacillus coagulans was lower in abundance in fecal samples that contained O157, while the genus Moryella spp was higher in abundance. The results of this dissertation highlight factors associated with O157 shedding by dairy cows and calves. This information may be used when developing techniques that reduce transmission between dairy cows, or dissemination of O157 beyond the dairy. Because O157 does not adversely affect cows, the future adoption of O157 mitigation strategies relies on whether or not these approaches benefit the dairy operation. Based on our results, we hypothesize that ill health and cow stress is associated with shedding, but is difficult to measure and monetarily quantify. At the current time, development of reduction strategies should focus on methods that reduce O157 while simultaneously improving cow health and production (e. g reducing stress during cow transition periods, improving passive transfer and limiting dam exposure of calves, feeding probiotics that improve GI health, creating multi-pathogen vaccines). We propose that future studies should also focus on determining whether O157 augments milk production and cow fertility.
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    Theory of graph traversal edit distance, extensions, and applications
    (Colorado State University. Libraries, 2019) Ebrahimpour Boroojeny, Ali, author; Chitsaz, Hamidreza, advisor; Ben-Hur, Asa, committee member; Abdo, Zaid, committee member
    Many problems in applied machine learning deal with graphs (also called networks), including social networks, security, web data mining, protein function prediction, and genome informatics. The kernel paradigm beautifully decouples the learning algorithm from the underlying geometric space, which renders graph kernels important for the aforementioned applications. In this paper, we give a new graph kernel which we call graph traversal edit distance (GTED). We introduce the GTED problem and give the first polynomial time algorithm for it. Informally, the graph traversal edit distance is the minimum edit distance between two strings formed by the edge labels of respective Eulerian traversals of the two graphs. Also, GTED is motivated by and provides the first mathematical formalism for sequence co-assembly and de novo variation detection in bioinformatics. We demonstrate that GTED admits a polynomial time algorithm using a linear program in the graph product space that is guaranteed to yield an integer solution. To the best of our knowledge, this is the first approach to this problem. We also give a linear programming relaxation algorithm for a lower bound on GTED. We use GTED as a graph kernel and evaluate it by computing the accuracy of an SVM classifier on a few datasets in the literature. Our results suggest that our kernel outperforms many of the common graph kernels in the tested datasets. As a second set of experiments, we successfully cluster viral genomes using GTED on their assembly graphs obtained from de novo assembly of next-generation sequencing reads. In this project, we also show how to solve the problems of local and semi-global alignment between two graphs. Finally, we suggest an approach for speeding up the computations using pre-assumption on a subset of nodes that have to be paired.
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    Time series analysis of limber pine (Pinus flexilis) health in the U.S. Rocky Mountains in response to white pine blister rust (Cronartium ribicola) and bark beetles
    (Colorado State University. Libraries, 2018) Leddy, K. A., author; Stewart, Jane E., advisor; Abdo, Zaid, committee member; Sloan, Dan, committee member; Schoettle, Anna, committee member; Liber, Howard, committee member
    From 2004-2007, 106 permanent limber pine monitoring plots were established and measured throughout the U.S. Rocky Mountains (MT, WY, CO) to characterize health trends in response to white pine blister rust (WPBR) and bark beetles (including mountain pine beetle, "MPB", and Ips spp., "Ips") over time. These plots were subsequently measured in 2011-2013 and again in 2016-17 to form a time series analysis of limber pine health. Data were gathered on 8,206 monumented trees (4,176 limber pine) and included measurements on various stand, ground cover, and landscape characteristics over the three time intervals. The overall percentage of live trees infected with WPBR was 29.4% in 2004-07 and 25.7% in 2016-17, with incidence decreasing in parts of Wyoming (Pole Mountain, Laramie Peak), increasing in southern Colorado (Sangre de Cristo Mountains), and stable in other subregions. However, of limber pines that were healthy during the first measurement, 22.2% were declining/dying and 21.1% had died by the end of the study period due to WPBR and/or bark beetle damages. Due to this, it is likely that new WPBR infections are occurring as the large number of live, infected trees dying during the survey may have masked newly infected trees in incidence calculations. In heavily WPBR-infected areas such as Pole Mountain, Wyoming, 65% of live trees were infected (in 2004-07), and of trees that began the study as healthy, 23% were declining or dying and 38% had died by the end of the study period (2016-17). Additionally, WPBR severity increased significantly from the beginning of the study with 4 previously uninfected sites gaining WPBR infections, 29 sites advancing to 'moderately infected' and 5 sites becoming 'heavily infected'. The overall average number of cankers per tree (3.5) was stable, but the number of infected limber pine with a canker in the lower 1/3 of the stem (18%) increased significantly (+4.2%, P = 0.001). When examining all limber pine in the study, 8%, 3% and 3% were killed by MPB/Ips., WPBR, and combined effects of these agents, respectively. Of the 887 live, but declining or dying limber pine, 52% had WPBR infections and 38% had damage from twig beetles (Pityophthorus spp., Pityogenes spp.) in 2016-17. Though all sites had ≥ 20% limber pine composition, 34% of sites had no limber pine regeneration and 7% had no regeneration of any tree species over the entirety of the study period. The results of this time series indicate that limber pine populations in the U.S. Rocky Mountains are declining due to effects from WPBR and MPB/Ips. Long-term surveys capture the effects of these damage agents on native tree populations and provide critical guidance for future management and restoration of these ecologically valuable species. Limber pine is at risk due to the various biotic and abiotic agents threatening their health. Thus, future directions involve restorative management practices for highly impacted areas where limber pine is a climax species and proactive management for healthy limber stands to promote resilience to likely damage agents. In highly impacted areas (WPBR incidence, mortality, or bark beetle damage on >50% of trees and low limber pine density and regeneration), where limber pine co-exists with other tree species, it may be favorable to allow the natural succession of other tree species to become dominant. However in xeric, harsh sites where limber pine is a climax species, these highly impacted areas are at-risk for losing all tree cover and should be considered for protective and restorative planting strategies. As natural resistance to WPBR occurs on the landscape, genetic screening and protection of mature limber pine carrying either complete or partial resistance to the pathogen should be pursued to preserve this genetic diversity. A priority should be to protect resistant against bark beetles and fire using established management practices. Additionally, seed-sourcing from resistant trees can allow for resistant progeny to be out-planted into high priority areas, thus buffering stands at risk for high WPBR mortality. Moreover management plans that promote diversification of age and diameter classes within stands can provide resilience against pest and pathogen attacks, as bark beetles vary in diameter preference and WPBR infections tend to cause higher mortality in smaller diameter trees. Lastly in healthy limber pine stands, proactive management of pest impacts to promote stand resilience is recommended as in Schoettle & Sniezko (2007) in order to preserve these healthy populations.