Browsing by Author "Hamerly, Timothy"

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Detection of Pseudomonas aeruginosa biomarkers from thermally injured mice in situ using imaging mass spectrometry
(2017-12) Hamerly, Timothy; Everett, Jake A.; Paris, Nina; Fisher, Steve T.; Karunamurthy, Arivarasan; James, Garth A.; Rumbaugh, Kendra P.; Rhoads, Daniel D.; Bothner, Brian
Monitoring patients with burn wounds for infection is standard practice because failure to rapidly and specifically identify a pathogen can result in poor clinical outcomes, including death. Therefore, a method that facilitates detection and identification of pathogens in situ within minutes of biopsy would be a significant benefit to clinicians. Mass spectrometry is rapidly becoming a standard tool in clinical settings, capable of identifying specific pathogens from complex samples. Imaging mass spectrometry (IMS) expands the information content by enabling spatial resolution of biomarkers in tissue samples as in histology, without the need for specific stains/antibodies. Herein, a murine model of thermal injury was used to study infection of burn tissue by Pseudomonas aeruginosa. This is the first use of IMS to detect P. aeruginosa infection in situ from thermally injured tissue. Multiple molecular features could be spatially resolved to infected or uninfected tissue. This demonstrates the potential use of IMS in a clinical setting to aid doctors in identifying both presence and species of pathogens in tissue.
Differences in amino acid catabolism by gut microbes with/without prebiotics inclusion in GDDY-based diet affect feed utilization in rainbow trout
(2017-09) Betiku, Omolola C.; Yeoman, Carl J.; Gaylord, T. Gibson; Duff, Glenn C.; Hamerly, Timothy; Bothner, Brian; Block, Stephanie S.; Sealey, Wendy M.
There is the need to enhance feed efficiency and growth of rainbow trout to reduce production costs of cultured fish. This study conducted a 3 × 4 factorial experiment with three graded levels of grain distiller dried yeast (GDDY) protein (0%, 50%, 75%) as replacement for fishmeal and four different prebiotics inclusion levels (0% (control), 0.4%, 1% mannooligosaccharides (MOS), and 1% GroBiotic A). The feeding trial was conducted for 12 weeks during which fish were fed daily to apparent satiation. Growth of rainbow trout was not affected by replacement of fishmeal with GDDY, but feed conversion ratio (P < 0.0001) was greater at the highest level of GDDY inclusion. Increasing GDDY inclusion significantly increased feed intake (P < 0.00015), which resulted in poor feed utilization. Acetic (P = 0.1994), propionic (P = 0.8037), butyric (P = 0.6268), valeric (P = 0.5877), and isovaleric (P = 0.5919) acids profiles did not differ by diet nor with inclusion of MOS or GroBiotic A. Whole shotgun metagenomic analyses of the gastrointestinal tract (GIT) microbiota revealed enrichment in the fungal phyla Ascomycota and Basidiomycota and the bacterial phylum Actinobacteria in the GDDY-fed fish compared to those fed the control fishmeal-based diet, which may be reflective of the species endogenous in GDDY. Microbial genes involved in branched-chain amino acid metabolism (glutamate, glutamine, aspartate) (P = 0.028) and glutamate dehydrogenase clusters (P = 0.0192), were also elevated in the fish fed the 75% GDDY-based diet. The results from this study indicate the potential for microbially-mediated catabolism of the non-essential amino acids, and suggest this activity may significantly influence efficient utilization of dietary nitrogen in the yeast-based protein diet.
Investigations into the Use of a Protein Sensor Assay for Metabolite Analysis
(2015-09) Hamerly, Timothy; Bothner, Brian
Rapid and definitive classification of biological samples has application in industrial, agricultural, and clinical settings. Considerable effort has been given to analytical methods to address such applications over the past 50 years, with the majority of successful solutions focusing on a single molecular target. However, in many cases, a single or even a few features are insufficient for accurate characterization or classification. Serum albumin (SA) proteins are a class of cargo-carrying proteins in blood that have evolved to transport a wide variety of metabolites and peptides in mammals. These proteins have up to seven binding sites which communicate allosterically to orchestrate a complex pick-up and delivery system involving a large number of different molecules at any time. The ability of SA proteins to bind multiple molecular species in a sophisticated manner inspired the development of assays to differentiate complex biological solutions. The combination of SA and high-resolution liquid chromatography mass spectrometry (LC-MS) is showing exciting promise as a protein sensor assay (PSA) for classification of complex biological samples. In this study, the PSA has been applied to cells undergoing and recovering from mild oxidative stress. Analysis using traditional LC-MS-based metabolomics failed to differentiate samples into treatment or temporal groups, whereas samples first treated with the PSA were cleanly classified into both correct treatment and temporal groups. The success of the PSA could be attributed to selective binding of metabolites, leading to a reduction in sample complexity and a general reduction in chemical noise. Metabolites important to successful sample classification were often enriched by 100-fold or more yet displayed a wide range of affinities for SA. The end result of PSA treatment is better classification of samples with a reduction in the number of features seen overall. Together, these results demonstrate how the use of a protein-based assay before LC-MS analysis can greatly improve separation and lead to more accurate and successful tracking of the metabolic state in an organism, suggesting potential application in a wide range of fields.
Multi-level Omics Analysis Provides Insight to the Ignicoccus hospitalis-Nanoarchaeum equitans Association
(2017-09) Rawle, Rachel A.; Hamerly, Timothy; Tripet, Brian P.; Giannone, Richard J.; Wurch, Louie; Hettich, Robert L.; Podar, Mircea; Copie, Valerie; Bothner, Brian
BACKGROUND Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted 'omics' analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. METHODS We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized using interaction maps generated using STRING. RESULTS Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis-N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. CONCLUSIONS This multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis-N. equitans association. GENERAL SIGNIFICANCE Our study applies statistical and visualization techniques to a mixed-source omics data set to yield a more global insight into a complex system, that was not readily discernable from separate omics studies.
Search for a Shared Genetic or Biochemical Basis for Biofilm Tolerance to Antibiotics across Bacterial Species
(American Society for Microbiology, 2022-04) Stewart, Philip S.; Williamson, Kerry S.; Boegli, Laura; Hamerly, Timothy; White, Ben; Scott, Liam; Hu, Xiao; Mumey, Brendan M.; Franklin, Michael J.; Bothner, Brian; Vital-Lopez, Francisco G.; Wallqvist, Anders; James, Garth A.
Is there a universal genetically programmed defense providing tolerance to antibiotics when bacteria grow as biofilms? A comparison between biofilms of three different bacterial species by transcriptomic and metabolomic approaches uncovered no evidence of one. Single-species biofilms of three bacterial species (Pseudomonas aeruginosa, Staphylococcus aureus, and Acinetobacter baumannii) were grown in vitro for 3 days and then challenged with respective antibiotics (ciprofloxacin, daptomycin, and tigecycline) for an additional 24 h. All three microorganisms displayed reduced susceptibility in biofilms compared to planktonic cultures. Global transcriptomic profiling of gene expression comparing biofilm to planktonic and antibiotic-treated biofilm to untreated biofilm was performed. Extracellular metabolites were measured to characterize the utilization of carbon sources between biofilms, treated biofilms, and planktonic cells. While all three bacteria exhibited a species-specific signature of stationary phase, no conserved gene, gene set, or common functional pathway could be identified that changed consistently across the three microorganisms. Across the three species, glucose consumption was increased in biofilms compared to planktonic cells, and alanine and aspartic acid utilization were decreased in biofilms compared to planktonic cells. The reasons for these changes were not readily apparent in the transcriptomes. No common shift in the utilization pattern of carbon sources was discerned when comparing untreated to antibiotic-exposed biofilms. Overall, our measurements do not support the existence of a common genetic or biochemical basis for biofilm tolerance against antibiotics. Rather, there are likely myriad genes, proteins, and metabolic pathways that influence the physiological state of individual microorganisms in biofilms and contribute to antibiotic tolerance.
Untargeted Metabolomics Studies Employing NMR and LC–MS Reveal Metabolic Coupling Between Nanoarcheum Equitans and Its Archaeal Host Ignicoccus Hospitalis
(2014-11) Hamerly, Timothy; Tripet, Brian P.; Tigges, Michelle M.; Giannone, Richard J.; Wurch, Louie; Hettich, Robert L.; Podar, Mircea; Copie, Valerie; Bothner, Brian
Abstract Interspecies interactions are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC–MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with informa-tion about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hosp-italis that are impacted by the presence of N. equitans, including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. This finding is based on N. equi-tans’s consumption of a significant fraction of the metab-olite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans. Combining LC–MS and NMR metabolomics datasets improved cov-erage of the metabolome and enhanced the identification and quantitation of cellular metabolites.