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The unicellular cyanobacterium Synechocystis sp. PCC 6803 contains a NiFe-type bidirectional hydrogenase that is capable of using reducing equivalents to reduce protons and generate H¬2. In order to achieve sustained H2 production using this cyanobacterium many challenges need to be overcome. Reported H2 production from Synechocystis is of low rate and often transient. Results described in this dissertation show that the hydrogenase activity in Synechocystis is quite different during periods of darkness and light. In darkness, the hydrogenase enzyme acts in a truly bidirectional way and a particular H2 concentration is reached that depends upon the amount of biomass involved in H2 production. On the other hand, in the presence of light the enzyme shows only transient H2 production followed by a rapid and constitutive H2 oxidation. H2 oxidation and production were measured from a variety of Synechocystis strains in which components of the photosynthetic or respiratory electron transport chain were either deleted or inhibited. It was shown that the light-induced H2 oxidation is dependent on the activity of cytochrome b6f and photosystem I but not on the activity of photosystem II, indicating a channeling of electrons through cytochrome b6f and photosystem I. Because of the sequence similarities between subunits of NADH dehydrogenase I in E. coli and subunits of hydrogenase in Synechocystis, NADH dehydrogenase I was considered as the most likely candidate to mediate the electron transfer from hydrogenase to the membrane electron carrier plastoquinone, and a three-dimensional homology model with the associated subunits shows that structurally it is possible for the subunits of the two complexes to assemble. Finally, with the aim of improving the rate of H2 production in Synechocystis by using a powerful hydrogenase enzyme, a mutant strain of Synechocystis was created in which the native hydrogenase was replaced with the hydrogenase from Lyngbya aestuarii BL J, a strain with higher capacity for H2 production. H2 production was detected in this Synechocystis mutant strain, but only in the presence of external reductants. Overall, this study emphasizes the importance of redox partners in determining the direction of H2 flux in Synechocystis.
ContributorsDatta, Īpsitā (Author) / Vermaas, Willem Fj (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Rittmann, Bruce (Committee member) / Jones, Anne K (Committee member) / Arizona State University (Publisher)
Created2015
Description
The processes of a human somatic cell are very complex with various genetic mechanisms governing its fate. Such cells undergo various genetic mutations, which translate to the genetic aberrations that we see in cancer. There are more than 100 types of cancer, each having many more subtypes with aberrations being unique to each. In the past two decades, the widespread application of high-throughput genomic technologies, such as micro-arrays and next-generation sequencing, has led to the revelation of many such aberrations. Known types and subtypes can be readily identified using gene-expression profiling and more importantly, high-throughput genomic datasets have helped identify novel sub-types with distinct signatures. Recent studies showing usage of gene-expression profiling in clinical decision making in breast cancer patients underscore the utility of high-throughput datasets. Beyond prognosis, understanding the underlying cellular processes is essential for effective cancer treatment. Various high-throughput techniques are now available to look at a particular aspect of a genetic mechanism in cancer tissue. To look at these mechanisms individually is akin to looking at a broken watch; taking apart each of its parts, looking at them individually and finally making a list of all the faulty ones. Integrative approaches are needed to transform one-dimensional cancer signatures into multi-dimensional interaction and regulatory networks, consequently bettering our understanding of cellular processes in cancer. Here, I attempt to (i) address ways to effectively identify high quality variants when multiple assays on the same sample samples are available through two novel tools, snpSniffer and NGSPE; (ii) glean new biological insight into multiple myeloma through two novel integrative analysis approaches making use of disparate high-throughput datasets. While these methods focus on multiple myeloma datasets, the informatics approaches are applicable to all cancer datasets and will thus help advance cancer genomics.
ContributorsYellapantula, Venkata (Author) / Dinu, Valentin (Thesis advisor) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Keats, Jonathan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Genomic structural variation (SV) is defined as gross alterations in the genome broadly classified as insertions/duplications, deletions inversions and translocations. DNA sequencing ushered structural variant discovery beyond laboratory detection techniques to high resolution informatics approaches. Bioinformatics tools for computational discovery of SVs however are still missing variants in the complex cancer genome. This study aimed to define genomic context leading to tool failure and design novel algorithm addressing this context. Methods: The study tested the widely held but unproven hypothesis that tools fail to detect variants which lie in repeat regions. Publicly available 1000-Genomes dataset with experimentally validated variants was tested with SVDetect-tool for presence of true positives (TP) SVs versus false negative (FN) SVs, expecting that FNs would be overrepresented in repeat regions. Further, the novel algorithm designed to informatically capture the biological etiology of translocations (non-allelic homologous recombination and 3&ndashD; placement of chromosomes in cells –context) was tested using simulated dataset. Translocations were created in known translocation hotspots and the novel&ndashalgorithm; tool compared with SVDetect and BreakDancer. Results: 53% of false negative (FN) deletions were within repeat structure compared to 81% true positive (TP) deletions. Similarly, 33% FN insertions versus 42% TP, 26% FN duplication versus 57% TP and 54% FN novel sequences versus 62% TP were within repeats. Repeat structure was not driving the tool's inability to detect variants and could not be used as context. The novel algorithm with a redefined context, when tested against SVDetect and BreakDancer was able to detect 10/10 simulated translocations with 30X coverage dataset and 100% allele frequency, while SVDetect captured 4/10 and BreakDancer detected 6/10. For 15X coverage dataset with 100% allele frequency, novel algorithm was able to detect all ten translocations albeit with fewer reads supporting the same. BreakDancer detected 4/10 and SVDetect detected 2/10 Conclusion: This study showed that presence of repetitive elements in general within a structural variant did not influence the tool's ability to capture it. This context-based algorithm proved better than current tools even with half the genome coverage than accepted protocol and provides an important first step for novel translocation discovery in cancer genome.
ContributorsShetty, Sheetal (Author) / Dinu, Valentin (Thesis advisor) / Bussey, Kimberly (Committee member) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Arizona State University (Publisher)
Created2014
Description
Skeletal muscle (SM) mitochondria generate the majority of adenosine triphosphate (ATP) in SM, and help regulate whole-body energy expenditure. Obesity is associated with alterations in SM mitochondria, which are unique with respect to their arrangement within cells; some mitochondria are located directly beneath the sarcolemma (i.e., subsarcolemmal (SS) mitochondria), while other are nested between the myofibrils (i.e., intermyofibrillar (IMF) mitochondria). Functional and proteome differences specific to SS versus IMF mitochondria in obese individuals may contribute to reduced capacity for muscle ATP production seen in obesity. The overall goals of this work were to (1) isolate functional muscle SS and IMF mitochondria from lean and obese individuals, (2) assess enzyme activities associated with the electron transport chain and ATP production, (3) determine if elevated plasma amino acids enhance SS and IMF mitochondrial respiration and ATP production rates in SM of obese humans, and (4) determine differences in mitochondrial proteome regulating energy metabolism and key biological processes associated with SS and IMF mitochondria between lean and obese humans.
Polarography was used to determine functional differences in isolated SS and IMF mitochondria between lean (37 ± 3 yrs; n = 10) and obese (35 ± 3 yrs; n = 11) subjects during either saline (control) or amino acid (AA) infusions. AA infusion increased ADP-stimulated respiration (i.e., coupled respiration), non-ADP stimulated respiration (i.e., uncoupled respiration), and ATP production rates in SS, but not IMF mitochondria in lean (n = 10; P < 0.05). Neither infusion increased any of the above parameters in muscle SS or IMF mitochondria of the obese subjects.
Using label free quantitative mass spectrometry, we determined differences in proteomes of SM SS and IMF mitochondria between lean (33 ± 3 yrs; n = 16) and obese (32 ± 3 yrs; n = 17) subjects. Differentially-expressed mitochondrial proteins in SS versus IMF mitochondria of obese subjects were associated with biological processes that regulate: electron transport chain (P<0.0001), citric acid cycle (P<0.0001), oxidative phosphorylation (P<0.001), branched-chain amino acid degradation, (P<0.0001), and fatty acid degradation (P<0.001). Overall, these findings show that obesity is associated with redistribution of key biological processes within the mitochondrial reticulum responsible for regulating energy metabolism in human skeletal muscle.
Polarography was used to determine functional differences in isolated SS and IMF mitochondria between lean (37 ± 3 yrs; n = 10) and obese (35 ± 3 yrs; n = 11) subjects during either saline (control) or amino acid (AA) infusions. AA infusion increased ADP-stimulated respiration (i.e., coupled respiration), non-ADP stimulated respiration (i.e., uncoupled respiration), and ATP production rates in SS, but not IMF mitochondria in lean (n = 10; P < 0.05). Neither infusion increased any of the above parameters in muscle SS or IMF mitochondria of the obese subjects.
Using label free quantitative mass spectrometry, we determined differences in proteomes of SM SS and IMF mitochondria between lean (33 ± 3 yrs; n = 16) and obese (32 ± 3 yrs; n = 17) subjects. Differentially-expressed mitochondrial proteins in SS versus IMF mitochondria of obese subjects were associated with biological processes that regulate: electron transport chain (P<0.0001), citric acid cycle (P<0.0001), oxidative phosphorylation (P<0.001), branched-chain amino acid degradation, (P<0.0001), and fatty acid degradation (P<0.001). Overall, these findings show that obesity is associated with redistribution of key biological processes within the mitochondrial reticulum responsible for regulating energy metabolism in human skeletal muscle.
ContributorsKras, Katon Anthony (Author) / Katsanos, Christos (Thesis advisor) / Chandler, Douglas (Committee member) / Dinu, Valentin (Committee member) / Mor, Tsafrir S. (Committee member) / Arizona State University (Publisher)
Created2017
Description
Random forest (RF) is a popular and powerful technique nowadays. It can be used for classification, regression and unsupervised clustering. In its original form introduced by Leo Breiman, RF is used as a predictive model to generate predictions for new observations. Recent researches have proposed several methods based on RF for feature selection and for generating prediction intervals. However, they are limited in their applicability and accuracy. In this dissertation, RF is applied to build a predictive model for a complex dataset, and used as the basis for two novel methods for biomarker discovery and generating prediction interval.
Firstly, a biodosimetry is developed using RF to determine absorbed radiation dose from gene expression measured from blood samples of potentially exposed individuals. To improve the prediction accuracy of the biodosimetry, day-specific models were built to deal with day interaction effect and a technique of nested modeling was proposed. The nested models can fit this complex data of large variability and non-linear relationships.
Secondly, a panel of biomarkers was selected using a data-driven feature selection method as well as handpick, considering prior knowledge and other constraints. To incorporate domain knowledge, a method called Know-GRRF was developed based on guided regularized RF. This method can incorporate domain knowledge as a penalized term to regulate selection of candidate features in RF. It adds more flexibility to data-driven feature selection and can improve the interpretability of models. Know-GRRF showed significant improvement in cross-species prediction when cross-species correlation was used to guide selection of biomarkers. The method can also compete with existing methods using intrinsic data characteristics as alternative of domain knowledge in simulated datasets.
Lastly, a novel non-parametric method, RFerr, was developed to generate prediction interval using RF regression. This method is widely applicable to any predictive models and was shown to have better coverage and precision than existing methods on the real-world radiation dataset, as well as benchmark and simulated datasets.
Firstly, a biodosimetry is developed using RF to determine absorbed radiation dose from gene expression measured from blood samples of potentially exposed individuals. To improve the prediction accuracy of the biodosimetry, day-specific models were built to deal with day interaction effect and a technique of nested modeling was proposed. The nested models can fit this complex data of large variability and non-linear relationships.
Secondly, a panel of biomarkers was selected using a data-driven feature selection method as well as handpick, considering prior knowledge and other constraints. To incorporate domain knowledge, a method called Know-GRRF was developed based on guided regularized RF. This method can incorporate domain knowledge as a penalized term to regulate selection of candidate features in RF. It adds more flexibility to data-driven feature selection and can improve the interpretability of models. Know-GRRF showed significant improvement in cross-species prediction when cross-species correlation was used to guide selection of biomarkers. The method can also compete with existing methods using intrinsic data characteristics as alternative of domain knowledge in simulated datasets.
Lastly, a novel non-parametric method, RFerr, was developed to generate prediction interval using RF regression. This method is widely applicable to any predictive models and was shown to have better coverage and precision than existing methods on the real-world radiation dataset, as well as benchmark and simulated datasets.
ContributorsGuan, Xin (Author) / Liu, Li (Thesis advisor) / Runger, George C. (Thesis advisor) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2017
Description
Many acidic hot springs in Yellowstone National Park support microbial iron oxidation, reduction, or microbial iron redox cycling (MIRC), as determined by microcosm rate experiments. Microbial dissimilatory iron reduction (DIR) was detected in numerous systems with a pH < 4. Rates of DIR are influenced by the availability of ferric minerals and organic carbon. Microbial iron oxidation (MIO) was detected from pH 2 – 5.5. In systems with abundant Fe (II), dissolved oxygen controls the presence of MIO. Rates generally increase with increased Fe(II) concentrations, but rate constants are not significantly altered by additions of Fe(II). MIRC was detected in systems with abundant ferric mineral deposition.
The rates of microbial and abiological iron oxidation were determined in a variety of cold (T= 9-12°C), circumneutral (pH = 5.5-9) environments in the Swiss Alps. Rates of MIO were measured in systems up to a pH of 7.4; only abiotic processes were detected at higher pH values. Iron oxidizing bacteria (FeOB) were responsible for 39-89% of the net oxidation rate at locations where biological iron oxidation was detected. Members of putative iron oxidizing genera, especially Gallionella, are abundant in systems where MIO was measured. Speciation calculations reveal that ferrous iron typically exists as FeCO30, FeHCO3+, FeSO40 or Fe2+ in these systems. The presence of ferrous (bi)carbonate species appear to increase abiotic iron oxidation rates relative to locations without significant concentrations. This approach, integrating geochemistry, rates, and community composition, reveals biogeochemical conditions that permit MIO, and locations where the abiotic rate is too fast for the biotic process to compete.
For a reaction to provide habitability for microbes in a given environment, it must energy yield and this energy must dissipate slowly enough to remain bioavailable. Thermodynamic boundaries exist at conditions where reactions do not yield energy, and can be quantified by calculations of chemical energy. Likewise, kinetic boundaries exist at conditions where the abiotic reaction rate is so fast that reactants are not bioavailable; this boundary can be quantified by measurements biological and abiological rates. The first habitability maps were drawn, using iron oxidation as an example, by quantifying these boundaries in geochemical space.
The rates of microbial and abiological iron oxidation were determined in a variety of cold (T= 9-12°C), circumneutral (pH = 5.5-9) environments in the Swiss Alps. Rates of MIO were measured in systems up to a pH of 7.4; only abiotic processes were detected at higher pH values. Iron oxidizing bacteria (FeOB) were responsible for 39-89% of the net oxidation rate at locations where biological iron oxidation was detected. Members of putative iron oxidizing genera, especially Gallionella, are abundant in systems where MIO was measured. Speciation calculations reveal that ferrous iron typically exists as FeCO30, FeHCO3+, FeSO40 or Fe2+ in these systems. The presence of ferrous (bi)carbonate species appear to increase abiotic iron oxidation rates relative to locations without significant concentrations. This approach, integrating geochemistry, rates, and community composition, reveals biogeochemical conditions that permit MIO, and locations where the abiotic rate is too fast for the biotic process to compete.
For a reaction to provide habitability for microbes in a given environment, it must energy yield and this energy must dissipate slowly enough to remain bioavailable. Thermodynamic boundaries exist at conditions where reactions do not yield energy, and can be quantified by calculations of chemical energy. Likewise, kinetic boundaries exist at conditions where the abiotic reaction rate is so fast that reactants are not bioavailable; this boundary can be quantified by measurements biological and abiological rates. The first habitability maps were drawn, using iron oxidation as an example, by quantifying these boundaries in geochemical space.
ContributorsSt Clair, Brian (Author) / Shock, Everett L (Thesis advisor) / Anbar, Ariel (Committee member) / Garcia-Pichel, Ferran (Committee member) / Hartnett, Hilairy (Committee member) / Arizona State University (Publisher)
Created2017
Description
Obesity and its underlying insulin resistance are caused by environmental and genetic factors. DNA methylation provides a mechanism by which environmental factors can regulate transcriptional activity. The overall goal of the work herein was to (1) identify alterations in DNA methylation in human skeletal muscle with obesity and its underlying insulin resistance, (2) to determine if these changes in methylation can be altered through weight-loss induced by bariatric surgery, and (3) to identify DNA methylation biomarkers in whole blood that can be used as a surrogate for skeletal muscle.
Assessment of DNA methylation was performed on human skeletal muscle and blood using reduced representation bisulfite sequencing (RRBS) for high-throughput identification and pyrosequencing for site-specific confirmation. Sorbin and SH3 homology domain 3 (SORBS3) was identified in skeletal muscle to be increased in methylation (+5.0 to +24.4 %) in the promoter and 5’untranslated region (UTR) in the obese participants (n= 10) compared to lean (n=12), and this finding corresponded with a decrease in gene expression (fold change: -1.9, P=0.0001). Furthermore, SORBS3 was demonstrated in a separate cohort of morbidly obese participants (n=7) undergoing weight-loss induced by surgery, to decrease in methylation (-5.6 to -24.2%) and increase in gene expression (fold change: +1.7; P=0.05) post-surgery. Moreover, SORBS3 promoter methylation was demonstrated in vitro to inhibit transcriptional activity (P=0.000003). The methylation and transcriptional changes for SORBS3 were significantly (P≤0.05) correlated with obesity measures and fasting insulin levels. SORBS3 was not identified in the blood methylation analysis of lean (n=10) and obese (n=10) participants suggesting that it is a muscle specific marker. However, solute carrier family 19 member 1 (SLC19A1) was identified in blood and skeletal muscle to have decreased 5’UTR methylation in obese participants, and this was significantly (P≤0.05) predicted by insulin sensitivity.
These findings suggest SLC19A1 as a potential blood-based biomarker for obese, insulin resistant states. The collective findings of SORBS3 DNA methylation and gene expression present an exciting novel target in skeletal muscle for further understanding obesity and its underlying insulin resistance. Moreover, the dynamic changes to SORBS3 in response to metabolic improvements and weight-loss induced by surgery.
Assessment of DNA methylation was performed on human skeletal muscle and blood using reduced representation bisulfite sequencing (RRBS) for high-throughput identification and pyrosequencing for site-specific confirmation. Sorbin and SH3 homology domain 3 (SORBS3) was identified in skeletal muscle to be increased in methylation (+5.0 to +24.4 %) in the promoter and 5’untranslated region (UTR) in the obese participants (n= 10) compared to lean (n=12), and this finding corresponded with a decrease in gene expression (fold change: -1.9, P=0.0001). Furthermore, SORBS3 was demonstrated in a separate cohort of morbidly obese participants (n=7) undergoing weight-loss induced by surgery, to decrease in methylation (-5.6 to -24.2%) and increase in gene expression (fold change: +1.7; P=0.05) post-surgery. Moreover, SORBS3 promoter methylation was demonstrated in vitro to inhibit transcriptional activity (P=0.000003). The methylation and transcriptional changes for SORBS3 were significantly (P≤0.05) correlated with obesity measures and fasting insulin levels. SORBS3 was not identified in the blood methylation analysis of lean (n=10) and obese (n=10) participants suggesting that it is a muscle specific marker. However, solute carrier family 19 member 1 (SLC19A1) was identified in blood and skeletal muscle to have decreased 5’UTR methylation in obese participants, and this was significantly (P≤0.05) predicted by insulin sensitivity.
These findings suggest SLC19A1 as a potential blood-based biomarker for obese, insulin resistant states. The collective findings of SORBS3 DNA methylation and gene expression present an exciting novel target in skeletal muscle for further understanding obesity and its underlying insulin resistance. Moreover, the dynamic changes to SORBS3 in response to metabolic improvements and weight-loss induced by surgery.
ContributorsDay, Samantha Elaine (Author) / Coletta, Dawn K. (Thesis advisor) / Katsanos, Christos (Committee member) / Mandarino, Lawrence J. (Committee member) / Shaibi, Gabriel Q. (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2017
Description
Rewired biological pathways and/or rewired microRNA (miRNA)-mRNA interactions might also influence the activity of biological pathways. Here, rewired biological pathways is defined as differential (rewiring) effect of genes on the topology of biological pathways between controls and cases. Similarly, rewired miRNA-mRNA interactions are defined as the differential (rewiring) effects of miRNAs on the topology of biological pathways between controls and cases. In the dissertation, it is discussed that how rewired biological pathways (Chapter 1) and/or rewired miRNA-mRNA interactions (Chapter 2) aberrantly influence the activity of biological pathways and their association with disease.
This dissertation proposes two PageRank-based analytical methods, Pathways of Topological Rank Analysis (PoTRA) and miR2Pathway, discussed in Chapter 1 and Chapter 2, respectively. PoTRA focuses on detecting pathways with an altered number of hub genes in corresponding pathways between two phenotypes. The basis for PoTRA is that the loss of connectivity is a common topological trait of cancer networks, as well as the prior knowledge that a normal biological network is a scale-free network whose degree distribution follows a power law where a small number of nodes are hubs and a large number of nodes are non-hubs. However, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the scale-free structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal samples. Hence, it is hypothesized that if the number of hub genes is different in a pathway between normal and cancer, this pathway might be involved in cancer. MiR2Pathway focuses on quantifying the differential effects of miRNAs on the activity of a biological pathway when miRNA-mRNA connections are altered from normal to disease and rank disease risk of rewired miRNA-mediated biological pathways. This dissertation explores how rewired gene-gene interactions and rewired miRNA-mRNA interactions lead to aberrant activity of biological pathways, and rank pathways for their disease risk. The two methods proposed here can be used to complement existing genomics analysis methods to facilitate the study of biological mechanisms behind disease at the systems-level.
This dissertation proposes two PageRank-based analytical methods, Pathways of Topological Rank Analysis (PoTRA) and miR2Pathway, discussed in Chapter 1 and Chapter 2, respectively. PoTRA focuses on detecting pathways with an altered number of hub genes in corresponding pathways between two phenotypes. The basis for PoTRA is that the loss of connectivity is a common topological trait of cancer networks, as well as the prior knowledge that a normal biological network is a scale-free network whose degree distribution follows a power law where a small number of nodes are hubs and a large number of nodes are non-hubs. However, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the scale-free structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal samples. Hence, it is hypothesized that if the number of hub genes is different in a pathway between normal and cancer, this pathway might be involved in cancer. MiR2Pathway focuses on quantifying the differential effects of miRNAs on the activity of a biological pathway when miRNA-mRNA connections are altered from normal to disease and rank disease risk of rewired miRNA-mediated biological pathways. This dissertation explores how rewired gene-gene interactions and rewired miRNA-mRNA interactions lead to aberrant activity of biological pathways, and rank pathways for their disease risk. The two methods proposed here can be used to complement existing genomics analysis methods to facilitate the study of biological mechanisms behind disease at the systems-level.
ContributorsLi, Chaoxing (Author) / Dinu, Valentin (Thesis advisor) / Kuang, Yang (Thesis advisor) / Liu, Li (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2017
Description
Biological soil crusts (biocrust) are photosynthetic communities of organisms forming in the top millimeters of unvegetated soil. Because soil crusts contribute several ecosystem services to the areas they inhabit, their loss under anthropogenic pressure has negative ecological consequences. There is a considerable interest in developing technologies for biocrust restoration such as biocrust nurseries to grow viable inoculum and the optimization of techniques for field deployment of this inoculum. For the latter, knowledge of the natural rates of biocrust dispersal is needed. Lateral dispersal can be based on self-propelled motility by component microbes, or on passive transport through propagule entrainment in runoff water or wind currents, all of which remain to be assessed. I focused my research on determining the capacity of biocrust for lateral self-propelled dispersal. Over the course of one year, I set up two greenhouse experiments where sterile soil substrates were inoculated with biocrusts and where the lateral advancement of biocrust and their cyanobacteria was monitored using time-course photography, discrete determination of soil chlorophyll a concentration, and microscopic observations. Appropriate uninoculated controls were also set up and monitored. These experiments confirm that cyanobacterial biological soil crusts are capable of laterally expanding when provided with presumably optimal watering regime similar to field conditions and moderate temperatures. The maximum temperatures of Sonoran Desert summer (up to 42 °C), exacerbated in the greenhouse setting (48 °C), caused a loss of biomass and the cessation of lateral dispersal, which resumed as temperature decreased. In 8 independent experiments, biocrust communities advanced laterally at an average rate of 2 cm per month, which is half the maximal rate possible based on the instantaneous speed of gliding motility of the cyanobacterium Microcoleus vaginatus. In a span of three months, populations of M. vaginatus, M. steenstrupii, and Scytonema spp. advanced 1 cm/month on average. The advancing crust front was found to be preferentially composed of hormogonia (differentiated, fast-gliding propagules of cyanobacteria). Having established the potential for laterally self-propelled community dispersal (without wind or runoff contributions) will help inform restoration efforts by proposing minimal inoculum size and optimal distance between inoculum patches.
ContributorsSorochkina, Kira (Author) / Garcia-Pichel, Ferran (Thesis advisor) / Rowe, Helen (Committee member) / Wu, Jianguo (Committee member) / Arizona State University (Publisher)
Created2017
Description
Decay of plant litter represents an enormous pathway for carbon (C) into the atmosphere but our understanding of the mechanisms driving this process is particularly limited in drylands. While microbes are a dominant driver of litter decay in most ecosystems, their significance in drylands is not well understood and abiotic drivers such as photodegradation are commonly perceived to be more important. I assessed the significance of microbes to the decay of plant litter in the Sonoran Desert. I found that the variation in decay among 16 leaf litter types was correlated with microbial respiration rates (i.e. CO2 emission) from litter, and rates were strongly correlated with water-vapor sorption rates of litter. Water-vapor sorption during high-humidity periods activates microbes and subsequent respiration appears to be a significant decay mechanism. I also found that exposure to sunlight accelerated litter decay (i.e. photodegradation) and enhanced subsequent respiration rates of litter. The abundance of bacteria (but not fungi) on the surface of litter exposed to sunlight was strongly correlated with respiration rates, as well as litter decay, implying that exposure to sunlight facilitated activity of surface bacteria which were responsible for faster decay. I also assessed the response of respiration to temperature and moisture content (MC) of litter, as well as the relationship between relative humidity and MC. There was a peak in respiration rates between 35-40oC, and, unexpectedly, rates increased from 55 to 70oC with the highest peak at 70oC, suggesting the presence of thermophilic microbes or heat-tolerant enzymes. Respiration rates increased exponentially with MC, and MC was strongly correlated with relative humidity. I used these relationships, along with litter microclimate and C loss data to estimate the contribution of this pathway to litter C loss over 34 months. Respiration was responsible for 24% of the total C lost from litter – this represents a substantial pathway for C loss, over twice as large as the combination of thermal and photochemical abiotic emission. My findings elucidate two mechanisms that explain why microbial drivers were more significant than commonly assumed: activation of microbes via water-vapor sorption and high respiration rates at high temperatures.
ContributorsTomes, Alexander (Author) / Day, Thomas (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Ball, Becky (Committee member) / Hall, Sharon (Committee member) / Roberson, Robert (Committee member) / Arizona State University (Publisher)
Created2020