Mycobacterium tuberculosis proteins involved in cell wall lipid biosynthesis improve BCG vaccine efficacy in a murine TB model

OBJECTIVES: Advances in tuberculosis (TB) vaccine development are urgently required to enhance global disease management. We evaluated the potential of Mycobacterium tuberculosis (M. tb)-derived protein antigens Rv0447c, Rv2957 and Rv2958c to boost BCG vaccine efficacy in the presence or absence of glucopyranosyl lipid adjuvant formulated in a stable emulsion (GLA-SE) adjuvant. METHODS: Mice received the BCG vaccine, followed by Rv0447c, Rv2957 and Rv2958c protein boosting with or without GLA-SE adjuvant 3 and 6 weeks later. Immune responses were examined at given time points. 9 weeks post vaccination, mice were aerosol-challenged with M. tb, and sacrificed at 6 and 12 weeks to assess bacterial burden. RESULTS: Vaccination of mice with BCG and M. tb proteins in the presence of GLA-SE adjuvant triggered strong IFN-γ and IL-2 production by splenocytes; more TNF-α was produced without GLA-SE addition. Antibody responses to all three antigens did not differ, with or without GLA-SE adjuvant. Protein boosting without GLA-SE adjuvant resulted in vaccinated animals having better control of pulmonary M. tb load at 6 and 12 weeks post aerosol infection, while animals receiving the protein boost with GLA-SE adjuvant exhibited more bacteria in the lungs. CONCLUSIONS: Our data provides evidence for developing Rv2958c, Rv2957 and Rv0447c in a heterologous prime-boost vaccination strategy with BCG

Cell stemness is maintained upon concurrent expression of RB and the mitochondrial ribosomal protein S18-2

Stemness encompasses the capability of a cell for self-renewal and differentiation. The stem cell maintains a balance between proliferation, quiescence, and regeneration via interactions with the microenvironment. Previously, we showed that ectopic expression of the mitochondrial ribosomal protein S18-2 (MRPS18-2) led to immortalization of primary fibroblasts, accompanied by induction of an embryonic stem cell (ESC) phenotype. Moreover, we demonstrated interaction between S18-2 and the retinoblastoma-associated protein (RB) and hypothesized that the simultaneous expression of RB and S18-2 is essential for maintaining cell stemness. Here, we experimentally investigated the role of S18-2 in cell stemness and differentiation. Concurrent expression of RB and S18-2 resulted in immortalization of Rb1−/− primary mouse embryonic fibroblasts and in aggressive tumor growth in severe combined immunodeficiency mice. These cells, which express both RB and S18-2 at high levels, exhibited the potential to differentiate into various lineages in vitro, including osteogenic, chondrogenic, and adipogenic lineages. Mechanistically, S18-2 formed a multimeric protein complex with prohibitin and the ring finger protein 2 (RNF2). This molecular complex increased the monoubiquitination of histone H2ALys119, a characteristic trait of ESCs, by enhanced E3-ligase activity of RNF2. Furthermore, we found enrichment of KLF4 at the S18-2 promoter region and that the S18-2 expression is positively correlated with KLF4 levels. Importantly, knockdown of S18-2 in zebrafish larvae led to embryonic lethality. Collectively, our findings suggest an important role for S18-2 in cell stemness and differentiation and potentially also in cancerogenesis

Metabolomics with LC-QTOF-MS Permits the Prediction of Disease Stage in Aortic Abdominal Aneurysm Based on Plasma Metabolic Fingerprint

Abdominal aortic aneurysm (AAA) is a permanent and localized aortic dilation, defined as aortic diameter ≥3 cm. It is an asymptomatic but potentially fatal condition because progressive enlargement of the abdominal aorta is spontaneously evolving towards rupture

Vertebrate Paralogous MEF2 Genes: Origin, Conservation, and Evolution

BACKGROUND: The myocyte enhancer factor 2 (MEF2) gene family is broadly expressed during the development and maintenance of muscle cells. Although a great deal has been elucidated concerning MEF2 transcription factors' regulation of specific gene expression in diverse programs and adaptive responses, little is known about the origin and evolution of the four members of the MEF2 gene family in vertebrates. METHODOLOGY/PRINCIPAL FINDINGS: By phylogenetic analyses, we investigated the origin, conservation, and evolution of the four MEF2 genes. First, among the four MEF2 paralogous branches, MEF2B is clearly distant from the other three branches in vertebrates, mainly because it lacks the HJURP_C (Holliday junction recognition protein C-terminal) region. Second, three duplication events might have occurred to produce the four MEF2 paralogous genes and the latest duplication event occurred near the origin of vertebrates producing MEF2A and MEF2C. Third, the ratio (K(a)/K(s)) of non-synonymous to synonymous nucleotide substitution rates showed that MEF2B evolves faster than the other three MEF2 proteins despite purifying selection on all of the four MEF2 branches. Moreover, a pair model of M0 versus M3 showed that variable selection exists among MEF2 proteins, and branch-site analysis presented that sites 53 and 64 along the MEF2B branch are under positive selection. Finally, and interestingly, substitution rates showed that type II MADS genes (i.e., MEF2-like genes) evolve as slowly as type I MADS genes (i.e., SRF-like genes) in animals, which is inconsistent with the fact that type II MADS genes evolve much slower than type I MADS genes in plants. CONCLUSION: Our findings shed light on the relationship of MEF2A, B, C, and D with functional conservation and evolution in vertebrates. This study provides a rationale for future experimental design to investigate distinct but overlapping regulatory roles of the four MEF2 genes in various tissues

Оценка надежности высоконадежных систем с учетом ЗИП

Предложены приближенные верхние и нижние оценки коэффициента готовности высоконадежной восстанавливаемой системы со структурной избыточностью. Полученные расчетные соотношения могут использоваться для оценки надежности высоконадежных систем с учетом различных стратегий пополнения ЗИП

Neuronal cell-based high-throughput screen for enhancers of mitochondrial function reveals luteolin as a modulator of mitochondria-endoplasmic reticulum coupling

Background: Mitochondrial dysfunction is a common feature of aging, neurodegeneration, and metabolic diseases. Hence, mitotherapeutics may be valuable disease modifiers for a large number of conditions. In this study, we have set up a large-scale screening platform for mitochondrial-based modulators with promising therapeutic potential. Results: Using differentiated human neuroblastoma cells, we screened 1200 FDA-approved compounds and identified 61 molecules that significantly increased cellular ATP without any cytotoxic effect. Following dose response curve-dependent selection, we identified the flavonoid luteolin as a primary hit. Further validation in neuronal models indicated that luteolin increased mitochondrial respiration in primary neurons, despite not affecting mitochondrial mass, structure, or mitochondria-derived reactive oxygen species. However, we found that luteolin increased contacts between mitochondria and endoplasmic reticulum (ER), contributing to increased mitochondrial calcium (Ca2+) and Ca2+-dependent pyruvate dehydrogenase activity. This signaling pathway likely contributed to the observed effect of luteolin on enhanced mitochondrial complexes I and II activities. Importantly, we observed that increased mitochondrial functions were dependent on the activity of ER Ca2+-releasing channels inositol 1,4,5-trisphosphate receptors (IP3Rs) both in neurons and in isolated synaptosomes. Additionally, luteolin treatment improved mitochondrial and locomotory activities in primary neurons and Caenorhabditis elegans expressing an expanded polyglutamine tract of the huntingtin protein. Conclusion: We provide a new screening platform for drug discovery validated in vitro and ex vivo. In addition, we describe a novel mechanism through which luteolin modulates mitochondrial activity in neuronal models with potential therapeutic validity for treatment of a variety of human diseases

DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning.

Recent technological advances have enabled DNA methylation to be assayed at single-cell resolution. However, current protocols are limited by incomplete CpG coverage and hence methods to predict missing methylation states are critical to enable genome-wide analyses. We report DeepCpG, a computational approach based on deep neural networks to predict methylation states in single cells. We evaluate DeepCpG on single-cell methylation data from five cell types generated using alternative sequencing protocols. DeepCpG yields substantially more accurate predictions than previous methods. Additionally, we show that the model parameters can be interpreted, thereby providing insights into how sequence composition affects methylation variability