A novel, highly sensitive, one-tube nested quantitative real-time PCR for Brucella in human blood samples.

IMPORTANCE: This study developed a highly sensitive and efficient method for the detection of brucellosis by introducing a one-tube nested quantitative real-time PCR (qPCR) approach, representing a remarkable advance in the field. The method demonstrated an impressive analytical sensitivity of 100 fg/µL, surpassing conventional qPCR and enabling the detection of even low levels of Brucella DNA. In addition, the study's comprehensive evaluation of 250 clinical samples revealed a specificity of 100% and a sensitivity of 98.6%, underscoring its reliability and accuracy. Most importantly, the new method significantly improved the detection rate of low-burden samples, reducing cycle threshold values by an average of 6.4. These results underscore the immense potential of this approach to facilitate rapid and accurate brucellosis diagnosis, which is critical for effective disease management and control.

CYP11B1 gene polymorphisms and susceptibility to ischemic stroke in a Chinese Han population.

Objectives: Ischemic stroke (IS) is the major cause of death and disability. While previous studies confirmed that CYP11B1 is closely associated with IS, the present study aimed to analyze the impact of CYP11B1 gene polymorphisms on the IS susceptibility. Methods: The present study genotyped six single nucleotide polymorphisms (SNPs) (including rs4736312, rs5017238, rs5301, rs5283, rs6410, and rs4534) of CYP11B1 in peripheral blood samples from IS and control populations. Logistic regression analysis was used to analyze the association between the SNPs and IS risk. The multifactor dimensionality reduction (MDR) method was used to determine the roles of SNP-SNP interactions in IS. Results: The present study showed that rs5283 was associated with an increased susceptibility to IS [odds ratio (OR) 1.81, p = 0.012]. On the contrary, rs6410 had a protective influence on IS risk (OR 0.56, p = 0.020). Stratified analyses indicated that rs5283 could enhance the risk of IS in subjects aged >63 years (OR 2.41, p = 0.011), of female gender (OR 3.31, p = 0.001), that do not smoke (OR 1.64, p = 0.005), and with hypertension (OR 2.07, p = 0.003). Whereas, rs6410 was related to a lower susceptibility to IS in subjects aged >63 years (OR 0.43, p = 0.032), of female gender (OR 0.30, p = 0.006), do not smoke (OR 0.42, p = 0.017), and with hypertension (OR 0.52, p = 0.022). Besides, rs4736312 reduced the IS susceptibility in non-smokers (OR 0.69, p = 0.031). Rs4534 had a risk-decreasing impact on IS in non-drinking (OR 0.54, p = 0.016). Moreover, the results of the MDR analysis corroborate that the best prediction model for IS was rs5283. Conclusion: This study revealed that CYP11B1 gene polymorphisms strongly correlated with IS in the Chinese Han population.

Long noncoding RNA XIST: Mechanisms for X chromosome inactivation, roles in sex-biased diseases, and therapeutic opportunities.

Sexual dimorphism has been reported in various human diseases including autoimmune diseases, neurological diseases, pulmonary arterial hypertension, and some types of cancers, although the underlying mechanisms remain poorly understood. The long noncoding RNA (lncRNA) X-inactive specific transcript (XIST) is involved in X chromosome inactivation (XCI) in female placental mammals, a process that ensures the balanced expression dosage of X-linked genes between sexes. XIST is abnormally expressed in many sex-biased diseases. In addition, escape from XIST-mediated XCI and skewed XCI also contribute to sex-biased diseases. Therefore, its expression or modification can be regarded as a biomarker for the diagnosis and prognosis of many sex-biased diseases. Genetic manipulation of XIST expression can inhibit the progression of some of these diseases in animal models, and therefore XIST has been proposed as a potential therapeutic target. In this manuscript, we summarize the current knowledge about the mechanisms for XIST-mediated XCI and the roles of XIST in sex-biased diseases, and discuss potential therapeutic strategies targeting XIST.

Function of Host Protein Staufen1 in Rabies Virus Replication.

Rabies virus is a highly neurophilic negative-strand RNA virus with high lethality and remains a huge public health problem in developing countries to date. The double-stranded RNA-binding protein Staufen1 (STAU1) has multiple functions in RNA virus replication, transcription, and translation. However, its function in RABV infection and its mechanism of action are not clear. In this study, we investigated the role of host factor STAU1 in RABV infection of SH-SY-5Y cells. Immunofluorescence, TCID50 titers, confocal microscopy, quantitative real-time PCR and Western blotting were carried out to determine the molecular function and subcellular distribution of STAU1 in these cell lines. Expression of STAU1 in SH-SY-5Y cells was down-regulated by RNA interference or up-regulated by transfection of eukaryotic expression vectors. The results showed that N proficiently colocalized with STAU1 in SH-SY-5Y at 36 h post-infection, and the expression level of STAU1 was also proportional to the time of infection. Down-regulation of STAU1 expression increased the number of Negri body-like structures, enhanced viral replication, and a caused 10-fold increase in viral titers. Meanwhile, N protein and G protein mRNA levels also accumulated gradually with increasing infection time, which implied that STAU1 inhibited rabies virus infection of SH-SY-5Y cells in vitro. In conclusion, our results provide important clues for the detailed replication mechanism of rabies virus and the discovery of therapeutic targets.

Cell cycle-dependent and independent mating blocks ensure fungal zygote survival and ploidy maintenance.

To ensure genome stability, sexually reproducing organisms require that mating brings together exactly 2 haploid gametes and that meiosis occurs only in diploid zygotes. In the fission yeast Schizosaccharomyces pombe, fertilization triggers the Mei3-Pat1-Mei2 signaling cascade, which represses subsequent mating and initiates meiosis. Here, we establish a degron system to specifically degrade proteins postfusion and demonstrate that mating blocks not only safeguard zygote ploidy but also prevent lysis caused by aberrant fusion attempts. Using long-term imaging and flow-cytometry approaches, we identify previously unrecognized and independent roles for Mei3 and Mei2 in zygotes. We show that Mei3 promotes premeiotic S-phase independently of Mei2 and that cell cycle progression is both necessary and sufficient to reduce zygotic mating behaviors. Mei2 not only imposes the meiotic program and promotes the meiotic cycle, but also blocks mating behaviors independently of Mei3 and cell cycle progression. Thus, we find that fungi preserve zygote ploidy and survival by at least 2 mechanisms where the zygotic fate imposed by Mei2 and the cell cycle reentry triggered by Mei3 synergize to prevent zygotic mating.

Collagen type VI α5 gene variations may predict the risk of lung cancer development in Chinese Han population.

The abundant expression of collagen type VI α5 (COL6A5) exists in lung tissue, and its role in lung cancer is still unknown. We performed a genetic association study with an attempt to detect the relationships between single nucleotide polymorphisms (SNPs) in COL6A5 and lung cancer predisposition in Chinese Han population. We finally selected six tag-SNPs to determine their genotypes among 510 lung cancer patients and 495 healthy controls with the MassARRAY platform. The associations of SNPs and lung cancer risk were estimated by logistic regression method with adjustment for confounding factors. Two available databases were used for gene expression and prognosis analysis. COL6A5 rs13062453, rs1497305, and rs77123808 were significantly associated with the risk of lung cancer in the whole population or stratified subgroups (p < 0.05). Among them, COL6A5 rs13062453 and rs1497305 were also linked to the susceptibility of lung adenocarcinoma. Additionally, rs1497305 was found to be strongly related to the TNM staging under five genetic models (p < 0.05). Results from databases suggested the important role of COL6A5 in lung cancer development. COL6A5 polymorphisms rs13062453, rs1497305 and rs77123808 were associated with lung cancer risk in Chinese Han population. These findings first yield new insight of COL6A5 in lung cancer.

A toolbox of stable integration vectors in the fission yeast Schizosaccharomyces pombe.

Schizosaccharomyces pombe is a widely used model organism to study many aspects of eukaryotic cell physiology. Its popularity as an experimental system partially stems from the ease of genetic manipulations, where the innate homology-targeted repair is exploited to precisely edit the genome. While vectors to incorporate exogenous sequences into the chromosomes are available, most are poorly characterized. Here, we show that commonly used fission yeast vectors, which upon integration produce repetitive genomic regions, give rise to unstable genomic loci. We overcome this problem by designing a new series of stable integration vectors (SIVs) that target four different prototrophy genes. SIVs produce non-repetitive, stable genomic loci and integrate predominantly as single copy. Additionally, we develop a set of complementary auxotrophic alleles that preclude false-positive integration events. We expand the vector series to include antibiotic resistance markers, promoters, fluorescent tags and terminators, and build a highly modular toolbox to introduce heterologous sequences. Finally, as proof of concept, we generate a large set of ready-to-use, fluorescent probes to mark organelles and cellular processes with a wide range of applications in fission yeast research.This article has an associated First Person interview with the first author of the paper.

COL6A3 polymorphisms were associated with lung cancer risk in a Chinese population.

BACKGROUND: Lung cancer is one of the leading cause of cancer-related death in the world. Recently, many clinical researches have reported that COL6A3 had strong role in many diseases. The aim of this study was to evaluate the association between single nucleotide polymorphisms (SNPs) in COL6A3 and lung cancer susceptibility. METHOD: Eight variants in COL6A3 were genotyped in a Chinese Han population including 510 cases and 495 controls using Agena MassARRAY. Genetic models and haplotype analyses were used to calculate the association between COL6A3 SNPs and lung cancer risk. And we assessed the relative risk by the odds ratio (OR) and 95% confidence interval (CI). RESULTS: In our results, we observed that rs115510139 was linked to an increased risk of lung cancer in the codominant (adjusted OR = 1.61, 95%CI: 1.14-2.27, p = 0.007), dominant (adjusted OR = 1.36, 95%CI: 1.02-1.83, p = 0.037), recessive (adjusted OR = 1.41, 95%CI: 1.07-1.85, p = 0.015), and log-additive (adjusted OR = 1.27, 95%CI: 1.07-1.51, p = 0.006) models. After gender stratification analysis, we found that rs115510139, rs3736341 and rs12052971 were significant in males but were non-significant in females. Rs115510139 also can increase the risk of lung cancer in the population of age less than 61 years. When analyzed for the association with lung squamous carcinoma, rs13032404, rs115510139 and rs3736341 were related to the risk of lung cancer. CONCLUSIONS: Our findings indicated potential associations between COL6A3 polymorphisms and lung cancer risk, which may contribute to the identification of lung cancer patients in a Chinese population.

Impairing Cohesin Smc1/3 Head Engagement Compensates for the Lack of Eco1 Function.

The cohesin ring, which is composed of the Smc1, Smc3, and Scc1 subunits, topologically embraces two sister chromatids from S phase until anaphase to ensure their precise segregation to the daughter cells. The opening of the ring is required for its loading on the chromosomes and unloading by the action of Wpl1 protein. Both loading and unloading are dependent on ATP hydrolysis by the Smc1 and Smc3 "head" domains, which engage to form two composite ATPase sites. Based on the available structures, we modeled the Saccharomyces cerevisiae Smc1/Smc3 head heterodimer and discovered that the Smc1/Smc3 interfaces at the two ATPase sites differ in the extent of protein contacts and stability after ATP hydrolysis. We identified smc1 and smc3 mutations that disrupt one of the interfaces and block the Wpl1-mediated release of cohesin from DNA. Thus, we provide structural insights into how the cohesin heads engage with each other.

Characterization of a panARS-based episomal vector in the methylotrophic yeast Pichia pastoris for recombinant protein production and synthetic biology applications.

BACKGROUND: Recombinant protein production in the methylotrophic yeast Pichia pastoris largely relies on integrative vectors. Although the stability of integrated expression cassettes is well appreciated for most applications, the availability of reliable episomal vectors for this host would represent a useful tool to expedite cloning and high-throughput screening, ameliorating also the relatively high clonal variability reported in transformants from integrative vectors caused by off-target integration in the P. pastoris genome. Recently, heterologous and endogenous autonomously replicating sequences (ARS) were identified in P. pastoris by genome mining, opening the possibility of expanding the available toolbox to include efficient episomal plasmids. The aim of this technical report is to validate a 452-bp sequence ("panARS") in context of P. pastoris expression vectors, and to compare their performance to classical integrative plasmids. Moreover, we aimed to test if such episomal vectors would be suitable to sustain in vivo recombination, using fragments for transformation, directly in P. pastoris cells. RESULTS: A panARS-based episomal vector was evaluated using blue fluorescent protein (BFP) as a reporter gene. Normalized fluorescence from colonies carrying panARS-BFP outperformed the level of signal obtained from integrative controls by several-fold, whereas endogenous sequences, identified from the P. pastoris genome, were not as efficient in terms of protein production. At the single cell level, panARS-BFP clones showed lower interclonal variability but higher intraclonal variation compared to their integrative counterparts, supporting the idea that heterologous protein production could benefit from episomal plasmids. Finally, efficiency of 2-fragment and 3-fragment in vivo recombination was tested using varying lengths of overlapping regions and molar ratios between fragments. Upon optimization, minimal background was obtained for in vivo assembled vectors, suggesting this could be a quick and efficient method to generate of episomal plasmids of interest. CONCLUSIONS: An expression vector based on the panARS sequence was shown to outperform its integrative counterparts in terms of protein productivity and interclonal variability, facilitating recombinant protein expression and screening. Using optimized fragment lengths and ratios, it was possible to perform reliable in vivo recombination of fragments in P. pastoris. Taken together, these results support the applicability of panARS episomal vectors for synthetic biology approaches.

Adaptive Evolution: Don't Fix What's Broken.

Evolution of budding yeast after the removal of an important component of the polarization machinery, BEM1, followed reproducible evolutionary trajectories governed by epistasis. Interestingly, cells restored polarization not by finding a substitute for Bem1 but by rendering its function dispensable.

A Multi-Task Learning Framework for Head Pose Estimation under Target Motion.

Recently, head pose estimation (HPE) from low-resolution surveillance data has gained in importance. However, monocular and multi-view HPE approaches still work poorly under target motion, as facial appearance distorts owing to camera perspective and scale changes when a person moves around. To this end, we propose FEGA-MTL, a novel framework based on Multi-Task Learning (MTL) for classifying the head pose of a person who moves freely in an environment monitored by multiple, large field-of-view surveillance cameras. Upon partitioning the monitored scene into a dense uniform spatial grid, FEGA-MTL simultaneously clusters grid partitions into regions with similar facial appearance, while learning region-specific head pose classifiers. In the learning phase, guided by two graphs which a-priori model the similarity among (1) grid partitions based on camera geometry and (2) head pose classes, FEGA-MTL derives the optimal scene partitioning and associated pose classifiers. Upon determining the target's position using a person tracker at test time, the corresponding region-specific classifier is invoked for HPE. The FEGA-MTL framework naturally extends to a weakly supervised setting where the target's walking direction is employed as a proxy in lieu of head orientation. Experiments confirm that FEGA-MTL significantly outperforms competing single-task and multi-task learning methods in multi-view settings.

Gene Essentiality Is a Quantitative Property Linked to Cellular Evolvability.

Gene essentiality is typically determined by assessing the viability of the corresponding mutant cells, but this definition fails to account for the ability of cells to adaptively evolve to genetic perturbations. Here, we performed a stringent screen to assess the degree to which Saccharomyces cerevisiae cells can survive the deletion of ~1,000 individual "essential" genes and found that ~9% of these genetic perturbations could in fact be overcome by adaptive evolution. Our analyses uncovered a genome-wide gradient of gene essentiality, with certain essential cellular functions being more "evolvable" than others. Ploidy changes were prevalent among the evolved mutant strains, and aneuploidy of a specific chromosome was adaptive for a class of evolvable nucleoporin mutants. These data justify a quantitative redefinition of gene essentiality that incorporates both viability and evolvability of the corresponding mutant cells and will enable selection of therapeutic targets associated with lower risk of emergence of drug resistance.

Egocentric daily activity recognition via multitask clustering.

Recognizing human activities from videos is a fundamental research problem in computer vision. Recently, there has been a growing interest in analyzing human behavior from data collected with wearable cameras. First-person cameras continuously record several hours of their wearers' life. To cope with this vast amount of unlabeled and heterogeneous data, novel algorithmic solutions are required. In this paper, we propose a multitask clustering framework for activity of daily living analysis from visual data gathered from wearable cameras. Our intuition is that, even if the data are not annotated, it is possible to exploit the fact that the tasks of recognizing everyday activities of multiple individuals are related, since typically people perform the same actions in similar environments, e.g., people working in an office often read and write documents). In our framework, rather than clustering data from different users separately, we propose to look for clustering partitions which are coherent among related tasks. In particular, two novel multitask clustering algorithms, derived from a common optimization problem, are introduced. Our experimental evaluation, conducted both on synthetic data and on publicly available first-person vision data sets, shows that the proposed approach outperforms several single-task and multitask learning methods.

Event oriented dictionary learning for complex event detection.

Complex event detection is a retrieval task with the goal of finding videos of a particular event in a large-scale unconstrained Internet video archive, given example videos and text descriptions. Nowadays, different multimodal fusion schemes of low-level and high-level features are extensively investigated and evaluated for the complex event detection task. However, how to effectively select the high-level semantic meaningful concepts from a large pool to assist complex event detection is rarely studied in the literature. In this paper, we propose a novel strategy to automatically select semantic meaningful concepts for the event detection task based on both the events-kit text descriptions and the concepts high-level feature descriptions. Moreover, we introduce a novel event oriented dictionary representation based on the selected semantic concepts. Toward this goal, we leverage training images (frames) of selected concepts from the semantic indexing dataset with a pool of 346 concepts, into a novel supervised multitask lp -norm dictionary learning framework. Extensive experimental results on TRECVID multimedia event detection dataset demonstrate the efficacy of our proposed method.

Multitask linear discriminant analysis for view invariant action recognition.

Robust action recognition under viewpoint changes has received considerable attention recently. To this end, self-similarity matrices (SSMs) have been found to be effective view-invariant action descriptors. To enhance the performance of SSM-based methods, we propose multitask linear discriminant analysis (LDA), a novel multitask learning framework for multiview action recognition that allows for the sharing of discriminative SSM features among different views (i.e., tasks). Inspired by the mathematical connection between multivariate linear regression and LDA, we model multitask multiclass LDA as a single optimization problem by choosing an appropriate class indicator matrix. In particular, we propose two variants of graph-guided multitask LDA: 1) where the graph weights specifying view dependencies are fixed a priori and 2) where graph weights are flexibly learnt from the training data. We evaluate the proposed methods extensively on multiview RGB and RGBD video data sets, and experimental results confirm that the proposed approaches compare favorably with the state-of-the-art.