We investigated the behavioural mechanism underlying the recently discovered latitudinal variation in the social structure of the spider Anelosimus studiosus through population censuses, behavioural interaction trials, reciprocal nest transplants to different temperature environments and breeding experiments. Nest censuses completed at replicated sites at 2° changes in latitude between south Florida (26°) and east Tennessee (36°) indicated that the dominant social structure is a solitary female nest. Multifemale nests consisting of cooperative females and their young first appeared in the populations at 30° latitude and increased in frequency of representation with further increases in latitude as did number of females within multifemale nests. Interaction trials showed that communication and physical contact underlie the two social structures. Females from solitary female nests and F1 offspring reared in the laboratory demanded space (asocial phenotype), whereas individuals of multifemale nest origin (from same and foreign nests) were attracted to one another (social phenotype). Field experiments further showed that (1) individuals that dispersed from multifemale nests dispersed shorter distances and (2) nest coalescence was observed only at the higher latitudes, coincident with the presence of multifemale nests. Habitat transplants suggested that the behaviour underlying social structure is not plastic in this system, and breeding experiments eliminated a cryptic species alternative to the presence of different social structure phenotypes. Although both asocial and social phenotypes were present at all latitudes, the frequency of the social phenotype was rare at lower latitudes.

Indiana University-Purdue University Indianapolis (IUPUI) / Intervertebral discs (IVD) degenerate earlier than many other musculoskeletal tissues and will continue to degenerate with aging. IVD degeneration affects up to 80 percent of the adult population and is a major contributing factor to low back pain. Anti-sclerostin antibody is an FDA-approved treatment for osteoporosis in postmenopausal women at high-risk for fracture and, as a systemic stimulant of the Wnt/LRP5/β-Catenin signaling pathway, may impact the IVD. Stabilization of β-Catenin in the IVD increases Wnt signaling and is anabolic to the extracellular matrix (ECM), while deletion of β-catenin or LRP5 decreases Wnt signaling and is catabolic to the ECM. Here, we hypothesized that a reduction of Sost would stimulate ECM anabolism. Lumbar and caudal (tail) IVD and vertebrae of Sost KO and WT (wildtype) mice (n=8 each) were harvested at 16 weeks of age and tested by MRI, histology, immunohistochemistry, Western Blot, qPCR, and microCT. Compared to WT, Sost KO reduced sclerostin protein and Sost gene expression. Next, Sost KO increased the hydration of the IVD and the proteoglycan stain in the nucleus pulposus and decreased the expression of genes associated with IVD degeneration, e.g., heat shock proteins. However, deletion of Sost was compensated by less unphosphorylated (active) β-Catenin protein in the cell nucleus, upregulation of Wnt signaling inhibitors Dkk1 and sFRP4, and catabolic ECM gene expression. Consequently, notochordal and early chondrocyte-like cells (CLCs) were replaced by mature CLCs. Overall, Sost deletion increased hydration and proteoglycan protein content, but activated a compensatory suppression of Wnt signaling that may trigger chondrogenesis and may potentially be iatrogenic to the IVD in the long-term.

No description available.

Antimicrobial resistance (AMR) is a threat to global health, food security, and economic productivity. Infections caused by drug resistant Gram-negative pathogens, such as Escherichia coli, Pseudomonas aeruginosa, and Neisseria gonorrhoeae, are continuously becoming harder to treat due to limited treatment options and long turnaround times for culture-based phenotypic diagnosis. Alternatively, genotypic approaches that exploit whole genome sequencing have the potential to be faster and more accurate. Genotypic approaches rely on using bacterial genomes to predict AMR phenotypes. I generated a rules-based algorithm and machine learning models using known resistance determinants from bacterial genomes to predict resistance or susceptibility. I showed that machine learning was superior to a rules-based algorithm and achieved an average accuracy of 94% and 89% for E. coli and P. aeruginosa, respectively. These machine learning models identified novel AMR genotype-phenotype relationships between known resistance determinants and resistance phenotypes, which were experimentally validated. To identify the parameters that can improve machine learning models, I tested a variety of genetic features, algorithms, and evaluation metrics. I observed an intricate dependency between parameters for AMR prediction performance, illustrating that careful selection of parameters is required to generate accurate AMR prediction models. A limitation of this work was its prediction of resistance and susceptibility categories, as these are interpretations of minimum inhibitory concentrations defined by clinical breakpoint guidelines. Since multiple guidelines exist, these prediction models are not generalizable, so prediction of MIC values was explored. The average accuracy of my MIC prediction models was 86%, 41%, and 98% for E. coli, P. aeruginosa, and N. gonorrhoea, respectively. Despite the multifactorial and intricate nature of the resistome, I was able to accurately predict AMR phenotypes for many antibiotics for these pathogens. This is a step towards advanced diagnostic microbiology methods driven by genomics. / Thesis / Doctor of Philosophy (PhD) / Many surgeries, chemotherapy, and transplantation will be impossible if antibiotic resistance is not addressed. Antibiotic misuse, overuse, and time to definitive therapy exacerbate this global health problem. Phenotypic testing determines definitive therapy, but bacterial culturing is slow. A potentially faster and more accurate approach relies on sequencing the pathogen’s genome. I used machine learning to generate antibiotic resistance prediction models that achieved average accuracies of 94% and 89% for Escherichia coli and Pseudomonas aeruginosa, respectively. These models identified novel relationships between known resistance genes and resistance phenotypes, which were experimentally validated. Resistance and susceptibility are interpretations of a minimum inhibitory concentration (MIC) using a clinical breakpoint guideline. Since there are different guidelines, I generated MIC prediction models with average accuracies of 86%, 41%, and 98% for E. coli, P. aeruginosa, and Neisseria gonorrhoea, respectively. My findings work towards a world where clinical sequencing and genomics-based diagnostics are the gold standard.

Indiana University-Purdue University Indianapolis (IUPUI) / T helper cells play a crucial role in providing protection against a wide variety of pathogens. The differentiation and effector function of T helper cell subsets is dependent on cytokine activation of Signal Transducer and Activator of Transcription (STAT) family members. The development of Th17 cells, which are important for immunity to fungi and extracellular bacteria, relies on STAT3. We show that IL-23 in combination with IL-1β promotes maintenance of the Th17 phenotype following multiple rounds of stimulation. However, IL-23 does not promote commitment of Th17 cells, and when Th17 cells are cultured with IL-12 or IL-4 they switch to a Th1 and Th2 phenotype, respectively. The maintenance of the Th17 phenotype by IL-23 also requires STAT4. STAT4-deficient memory cells cultured with IL-23 have reduced IL-17 production following stimulation with either anti-CD3 or IL-18+IL-23 stimulation compared to wild type memory cells. Furthermore, STAT4-deficient mice have impaired in vivo Th17 development following immunization with ovalbumin. This challenges a one-STAT/one-subset paradigm and suggests that multiple STAT proteins can contribute to a single phenotype. To test this further we examined whether STAT3 is required for the development of Th2 cells, a subset known to depend upon the IL-4-induced activation of STAT6 for immunity to parasites and promoting allergic inflammation. We demonstrate that in the absence of STAT3, the expression of Th2-associated cytokines and transcription factors is dramatically reduced. STAT3 is also required for in vivo development of Th2 cells. Moreover, allergic inflammation is diminished in mice that have T cells lacking expression of STAT3. STAT3 does not affect STAT6 activation, but does impact how STAT6 functions in binding target genes. Thus, multiple STAT proteins can cooperate in promoting the development of specific T helper subsets.

No description available.

Background: Ischemic heart disease (IHD) is a leading cause of morbidity and mortality worldwide. Deprivation of oxygen/nutrients to the heart during IHD induces cardiac cell death resulting in an inflammatory response with the migration of neutrophils and macrophages, an essential process for cardiac repair. However, unresolved inflammation can cause adverse cardiac remodeling following myocardial ischemia/reperfusion (I/R) injury. Ubiquitin (UB) is an evolutionarily conserved protein. Previously, our lab has shown that exogenous UB treatment plays a cardioprotective role and significantly reduces infiltration of neutrophils and macrophages 3 days post-I/R injury in mice. Here, we investigated the role of exogenous UB in macrophage phenotype and function. It is hypothesized that exogenous UB modulates the phenotype and function of polarized M1 (pro-inflammatory), and/or M2 (anti-inflammatory) macrophages, thereby playing a cardioprotective role 3 days post-I/R. Methods: Isolated peritoneal macrophages (3 days post-thioglycolate injection) were pretreated with UB (20μg/mL) for 30 minutes followed by treatment with IFNγ (100U/mL), for M1 polarization, or IL-4 (20ng/mL), for M2 polarization for 72 hours. Polarized peritoneal macrophages were used to prepare cell lysates for western blot analyses, immunohistochemistry or migration. Plated and paraformaldehyde-fixed polarized peritoneal macrophages were stained with F4/80 to measure the cell spreading area. A scratch assay was used to measure polarized peritoneal macrophage migration. RAW264.7 macrophage cell line was used to assess polarized macrophage phagocytosis of pHrodo-conjugated E. coli bioparticles (100μg/mL). Results: Western blot analysis of polarized peritoneal macrophage lysates showed that UB treatment increased IFNγ-induced expression of iNOS (a marker of M1 phenotype). Treatment with UB decreased IFNγ induced-phosphorylation of STAT1 (transcription factor activated by IFNγ). IFNγ and IL-4 treatment decreased the expression of CXCR4 (receptor for UB). However, UB treatment had no effect on IFNγ and IL-4-mediated decrease in CXCR4 expression. Treatment with UB significantly reduced the cell spreading area of M1-polarized peritoneal macrophages. The migration of M1-polarized peritoneal macrophages was significantly increased with UB treatment. The migration of M2-polarized peritoneal macrophages was significantly greater compared to non-polarized control macrophages, and UB treatment had no effect on M2-polarized macrophage migration. In RAW264.7 cells, M1-polarized macrophages exhibited significantly increased phagocytosis of E. coli bioparticles vs. non-polarized control, and UB treatment enhanced M1-polarized macrophage phagocytosis. In contrast, UB treatment reduces the phagocytosis of E. coli bioparticles in M2-polarized macrophages. Conclusions: These findings indicate that treatment with exogenous UB can potentially alter the phenotype and function of M1- and M2-polarized macrophages.

No / Symptoms and signs (symptoms in brief) are the essential clinical manifestations for traditional Chinese medicine (TCM) diagnosis and treatments. To gain insights into the molecular mechanism of symptoms, this paper presents a network-based data mining method to integrate multiple phenotype-genotype data sources and predict the prioritizing gene rank list of symptoms. The result of this pilot study suggested some insights on the molecular mechanism of symptoms.

No description available.

No description available.