Browsing Department of molecular bacteriology (MOBA) by Subject (MeSH)
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An integrative computational approach to effectively guide experimental identification of regulatory elements in promoters.Transcriptional activity of genes depends on many factors like DNA motifs, conformational characteristics of DNA, melting etc. and there are computational approaches for their identification. However, in real applications, the number of predicted, for example, DNA motifs may be considerably large. In cases when various computational programs are applied, systematic experimental knock out of each of the potential elements obviously becomes nonproductive. Hence, one needs an approach that is able to integrate many heterogeneous computational methods and upon that suggest selected regulatory elements for experimental verification.
Optimizing Salmonella enterica serovar Typhimurium for bacteria-mediated tumor therapy.Bacteria-mediated tumor therapy using Salmonella enterica serovar Typhimurium is a therapeutic option with great potential. Numerous studies explored the potential of Salmonella Typhimurium for therapeutic applications, however reconciling safety with vectorial efficacy remains a major issue. Recently we have described a conditionally attenuated Salmonella vector that is based on genetic lipopolysaccharide modification. This vector combines strong attenuation with appropriate anti-tumor properties by targeting various cancerous tissues in vivo. Therefore, it was promoted as an anti-tumor agent. In this addendum, we summarize these findings and demonstrate additional optimization steps that may further improve the therapeutic efficacy of our vector strain.
Therapeutic Potential of Bacteria against Solid Tumors.Intentional bacterial infections can produce efficacious antitumor responses in mice, rats, dogs, and humans. However, low overall success rates and intense side effects prevent such approaches from being employed clinically. In this work, we titered bacteria and/or the proinflammatory cytokine TNFα in a set of established murine models of cancer. To interpret the experiments conducted, we considered and calibrated a tumor-effector cell recruitment model under the influence of functional tumor-associated vasculature. In this model, bacterial infections and TNFα enhanced immune activity and altered vascularization in the tumor bed. Information to predict bacterial therapy outcomes was provided by pretreatment tumor size and the underlying immune recruitment dynamics. Notably, increasing bacterial loads did not necessarily produce better long-term tumor control, suggesting that tumor sizes affected optimal bacterial loads. Short-term treatment responses were favored by high concentrations of effector cells postinjection, such as induced by higher bacterial loads, but in the longer term did not correlate with an effective restoration of immune surveillance. Overall, our findings suggested that a combination of intermediate bacterial loads with low levels TNFα administration could enable more favorable outcomes elicited by bacterial infections in tumor-bearing subjects. Cancer Res; 77(7); 1553-63. ©2017 AACR.