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Cardiac metabolism is deranged in heart failure, but underlying mechanisms remain unclear. Here, we show that lysine demethylase 8 (Kdm8) maintains an active mitochondrial gene network by repressing Tbx15, thus preventing dilated cardiomyopathy leading to lethal heart failure. Deletion of Kdm8 in mouse cardiomyocytes increased H3K36me2 with activation of Tbx15 and repression of target genes in the NAD+ pathway before dilated cardiomyopathy initiated. NAD+ supplementation prevented dilated cardiomyopathy in Kdm8 mutant mice, and TBX15 overexpression blunted NAD+-activated cardiomyocyte respiration. Furthermore, KDM8 was downregulated in human hearts affected by dilated cardiomyopathy, and higher TBX15 expression defines a subgroup of affected hearts with the strongest downregulation of genes encoding mitochondrial proteins. Thus, KDM8 represses TBX15 to maintain cardiac metabolism. Our results suggest that epigenetic dysregulation of metabolic gene networks initiates myocardium deterioration toward heart failure and could underlie heterogeneity of dilated cardiomyopathy.

Jielin Yang,1 XiaoJu Li,1 Lu Mao,1 Jiaxin Dong,1 Rong Fan,1 Liwen Zhang2 1Department of Public Health, Shihezi University School of Medicine, Xinjiang, People’s Republic of China; 2Department of Social Work, The First Affiliated Hospital of Shihezi University Medical College, Xinjiang, People’s Republic of ChinaCorrespondence: XiaoJu Li, Email Lixiaoju2007@sina.cnPurpose: This study aimed to assess the prevalence of depression in middle-aged and elderly patients with diabetes in China, determine the risk factors of depression in these patients, and explore the internal relationship between influencing factors and depression by constructing a pathway model.Methods: Data were collected from the 2018 China Health and Retirement Longitudinal Study (CHRLS). We included 1743 patients with diabetes who were assessed using the CES-D10, which is used to measure depressive symptoms in Chinese older adults. Based on the theory of psychological stress, data were analyzed using SPSS software version 22.0 and MPLUS 8.0. A correlation analysis was used to explore the relationship between the variables and depression scores. A path model was constructed to explore the interrelationships between variables and verify the relationships between variables and depression in patients with diabetes.Results: The prevalence of depression among patients with diabetes was 42.5%. The path analysis results showed that income, diabetes duration, sleep duration, pain distress, self-rated health, and glycemic control directly affected depression, and self-rated health had the largest effect value. With self-rated health and glycemic control as mediator variables, income, diabetes duration, sleep duration, pain distress, glycemic control, and insulin use had indirect effects on depression by influencing self-rated health. Age, frequency of blood glucose monitoring, and exercise glycemic control awareness indirectly affected depression by affecting glycemic control, self-rated health status, and depression.Conclusion: We found that the path analysis model could construct the interaction between the influencing factors and explore the potential interrelationship between the influencing factors and diabetes-related depression. Patients with diabetes must adhere to regular medication, maintain a healthy lifestyle, and have effective glycemic control. Diabetes depression can be effectively prevented by making psychological knowledge publicly available, providing health education, and establishing corresponding for diabetes.Keywords: diabetes, depression, influencing factors, path analysis

Background: Preeclampsia is an important clinical syndrome occurring during pregnancy. It shows genetic disposition, and the genetic risk has large ethnic heterogeneity. The study was designed to investigate the genetic risk of preeclampsia in Chinese pregnancies, and to apply it in early screening of the disease. Methods: We performed a genome-wide association study to screen candidate risk loci associated with preeclampsia in Chinese people, and validated them with an independent cohort of enlarged size. We also trained prediction models using the genotypes of newly identified risk loci to screen the pregnancies with high preeclampsia risk. Results: A segment in chromosome 6 covering HLA-DQB1, HLA-DRB5 and other immune-related genes shows the most significant association, and three loci in HLA-DRB5 were confirmed with an enlarged validation cohort. One of the validated loci, rs147440497, forms an amino acid change by the nucleotide polymorphism, which further causes a conformational change in the antigen-binding domain of HLA-DRB5 protein. With the genotypes of risk genetic loci and other demographic features, a machine-learning model was trained, which can predict Chinese preeclampsia pregnancies accurately, with a cross-validated recalling rate of 0.63 at a false positive rate of 8%. Conclusion: We identified a novel gene from maternal genome, HLA-DRB5, the polymorphism in which is associated with preeclampsia. The genotypes of risk SNP loci can also be used for prediction of preeclampsia risk in Chinese population accurately.

Gram-negative bacteria deliver effector proteins into eukaryotic host cells through type III and type IV secretion systems, causing infections and diseases. It remains unclear about the signals guiding the specific secretion of the effectors. Here, we adopted anin silicoapproach to analyze the mRNA sequences encoding the putative peptides essential for effective secretion and translocation of type III and IV effectors. A surprisingly high proportion of type III effectors showed tolerance on frameshift mutations in signal-encoding mRNA sequences, and in contrast, very low percentage of type IV effectors showed the similar frameshift tolerance. The type III effectors with frameshift tolerance of secretion signals were widely distributed in effector or signal families and bacterial species. Natural frameshifts could be identified in type III effector genes, which were often remedied in time by nearby paired insertions or deletions. Frameshift-derived peptide sequences also retained the common properties present in the signal peptides of raw type III effectors. Natural language processing models were adopted to represent the common features in the mRNA sequences encoding N-terminal peptides of type III effectors or C-terminal peptides of type IV effectors, with which transfer learning models could well predict the effectors, especially type IV effectors. The observations in the study would facilitate us understand the nature and evolution of secretion signals of type III and IV effectors.SignificanceIt has been a debate on the nature of signals for translocation of type III secreted effectors for a long time. Meanwhile, there has been no examination on the possibility of mRNA being as translocation signals for type IV or other types of secreted effectors. By computational simulation, the study demonstrated the protein nature of translocation signals for both type IV effectors and most type III effectors. Despite wide frameshift tolerance and atypical common features in mRNA sequences encoding the putative N-terminal signal sequences of type III effectors, more typical common physicochemical and amino acid composition properties between the mutation-derived and raw peptides, and the frequent self-correction phenomenon for naturally happening frameshifts supported the translocation signals at protein level of type III effectors. The common features in mRNA sequences encoding the translocation signal peptides of type III and IV effectors could also be combined in models for better prediction of the effectors respectively.

Background Paying attention to the health-related quality of life (HRQOL) of rural residents in poverty-stricken areas is an important part of China's poverty alleviation, but most studies on health-related quality of life have focused on rural residents, elderly individuals, and patients; evidence on the HRQOL of rural minority residents is limited. Thus, this study aimed to assess the HRQOL of rural Uighur residents in remote areas of Xinjiang, China, and determine its influencing factors to provide policy opinions for realizing a healthy China strategy. Methods A cross-sectional study was performed on 1019 Uighur residents in rural areas. The EQ-5D and self-administered questionnaires were used to assess HRQOL. We applied Tobit and binary logit regression models to analyse the factors influencing HRQOL among rural Uighur residents. Results The health utility index of the 1019 residents was − 0.197,1. The highest proportion of respondents reporting any problem was for mobility (57.5%), followed by usual activity (52.8%). Low levels of the five dimensions were related to age, smoking, sleep time, Daily intake of vegetables and fruit per capita. Gender, age, marital status, physical exercise, sleep duration, daily intake of cooking oil per capita, daily intake of fruit per capita, distance to the nearest medical institution, non-infectious chronic diseases (NCDs), self-rated health score, and participation in community activities were correlated with the health utility index of rural Uighur residents. Conclusions HRQOL was lower for rural Uyghur residents than for the general population. Improving health behavioural lifestyles and reducing the incidence of poverty (return to poverty) due to illness are effective means of promoting the health in Uyghur residents. The region must fulfil the health poverty alleviation policy and focus on vulnerable groups and low-income residents to improve the health, ability, opportunity, and confidence of this population to live well.

Background Depressive symptoms has become an increasingly important public health issue, contributing to disability and disease burden around the world. Studies have found that social support is strongly associated with depression in rural older people, so it is important to explore the factors influencing depression in rural older people in a comprehensive manner and to analyze the association between social support and depression. Methods On the basis of a theoretical model of health ecological, data were obtained from The China Health and Retirement Longitudinal Study in the 2018, with a sample consisting of 5,660 rural individuals aged ≥ 60 years. Then, Chi-square test and logistic regression analyses were used for statistical description and inference. Results Results indicate that the prevalence of depressive symptoms amongst rural older adults in China is 41.18%. The logistic regression analysis reveals that being female (OR = 1.406, 95% CI: 1.170–1.689), having ≥ 3 non-communicable diseases (OR = 1.736, 95% CI: 1.447–2.082), being not satisfied with spouse (OR = 2.978, 95% CI: 2.304–3.849), and being not at all satisfied with children (OR = 3.640, 95% CI: 1.736–7.635) are significantly correlated with depression. Conclusions The prevalence of depression amongst rural Chinese older adults is obviously high. Women and the elderly with chronic diseases need to be focused on. Hence, this study suggests that promoting interactivity amongst family members, increasing their relationship satisfaction, and encouraging active participation in social activities are necessary to further reduce the risk of depression amongst rural Chinese older adults. The government should not only improve the social security system, but also provide financial support and assistance to the elderly in rural China.

Stably Expressed Genes (SEGs) are a set of genes with invariant expression. Identification of SEGs, especially among both healthy and diseased tissues, is of clinical relevance to enable more accurate data integration, gene expression comparison and biomarker detection. However, it remains unclear how many global SEGs there are, whether there are development-, tissue- or cell-specific SEGs, and whether diseases can influence their expression. In this research, we systematically investigate human SEGs at single-cell level and observe their development-, tissue- and cell-specificity, and expression stability under various diseased states. A hierarchical strategy is proposed to identify a list of 408 spatial-temporal SEGs. Development-specific SEGs are also identified, with adult tissue-specific SEGs enriched with the function of immune processes and fetal tissue-specific SEGs enriched in RNA splicing activities. Cells of the same type within different tissues tend to show similar SEG composition profiles. Diseases or stresses do not show influence on the expression stableness of SEGs in various tissues. In addition to serving as markers and internal references for data normalization and integration, we examine another possible application of SEGs, i.e., being applied for cell decomposition. The deconvolution model could accurately predict the fractions of major immune cells in multiple independent testing datasets of peripheral blood samples. The study provides a reliable list of human SEGs at the single-cell level, facilitates the understanding on the property of SEGs, and extends their possible applications.

Background Escherichia coli O157:H7, being the cause of hemorrhagic colitis in humans, is recognized as one of the most dangerous and widespread foodborne pathogens. A highly specific, sensitive, and rapid E. coli O157:H7 detection method needs to be developed since the traditional detection methods are complex, costly, and time-consuming. Objective In this study, a recombinase aided amplification (RAA) assisted CRISPR/Cas12a (RAA-CRISPR/Cas12a) fluorescence platform for specific, sensitive, and rapid nucleic acid detection of E. coli O157:H7 was introduced. Methods First, the feasibility (components of CRISPR/Cas12a system) of the developed method was evaluated. Then a total of 34 bacterial strains were used for the specificity test, and gradient dilutions of extracted DNA and bacterial solutions of E. coli O157:H7 were prepared for the sensitivity test. Third, a real-time PCR assay for detection of the specific wzy gene of E. coli O157:H7 (FDA’s Bacteriological Analytical Manual) was used for sensitivity comparison. Finally, analysis of RAA-CRISPR/Cas12a detection in spiked and 93 real ground beef samples was carried out. Results The developed RAA-CRISPR/Cas12a method showed high specificity, and the detection could be completed within 30 min (after 4 h enrichment in spiked ground beef samples). The limit of detection (LOD) of bacterial concentrations and genomic DNA was 5.4 × 102 CFU/mL and 7.5 × 10−4 ng/μL, respectively, which exhibited higher sensitivity than the RAA-gel electrophoresis and RT-PCR methods. Furthermore, it was shown that E. coli O157:H7 in ground beef samples could be positively detected after 4 h enrichment when the initial bacterial inoculum was 9.0 CFU/25 g. The detection results of the RAA-CRISPR/Cas12a method were 100% consistent with those of the RT-PCR and traditional culture-based methods while screening the E. coli O157:H7 from 93 local collected ground beef samples. Conclusions The developed RAA-CRISPR/Cas12a method showed high specificity, high sensitivity, and rapid positive detection of E. coli O157:H7 from ground beef samples. Highlights The RAA-CRISPR/Cas12a system proposed in this study provided an alternative molecular tool for quick, specific, sensitive, and accurate detection of E. coli O157:H7 in foods.

We present a method for solving linear and nonlinear PDEs based on the variable projection (VarPro) framework and artificial neural networks (ANN). For linear PDEs, enforcing the boundary/initial value problem on the collocation points leads to a separable nonlinear least squares problem about the network coefficients. We reformulate this problem by the VarPro approach to eliminate the linear output-layer coefficients, leading to a reduced problem about the hidden-layer coefficients only. The reduced problem is solved first by the nonlinear least squares method to determine the hidden-layer coefficients, and then the output-layer coefficients are computed by the linear least squares method. For nonlinear PDEs, enforcing the boundary/initial value problem on the collocation points leads to a nonlinear least squares problem that is not separable, which precludes the VarPro strategy for such problems. To enable the VarPro approach for nonlinear PDEs, we first linearize the problem with a Newton iteration, using a particular form of linearization. The linearized system is solved by the VarPro framework together with ANNs. Upon convergence of the Newton iteration, the network coefficients provide the representation of the solution field to the original nonlinear problem. We present ample numerical examples with linear and nonlinear PDEs to demonstrate the performance of the method herein. For smooth field solutions, the errors of the current method decrease exponentially as the number of collocation points or the number of output-layer coefficients increases. We compare the current method with the ELM method from a previous work. Under identical conditions and network configurations, the current method exhibits an accuracy significantly superior to the ELM method., Comment: 35 pages, 18 figures, 10 tables

Increasing access to modern clinical practices concomitantly extends lifespan, ironically revealing new classes of degenerative and inflammatory diseases of later years. Here, an electronic graphene field-effect transistor (gFET) is reported, termed EV-chip, for label-free, rapid identification and quantification of exosomes (EV) associated with aging through specific surface markers, CD63 and CD151. Studies suggest that blood-derived exosomes carry specific biomolecules that can be used toward diagnostic applications of age and health. However, to observe improvements in patient outcomes, earlier detection at the point-of-care (POC) is required. Unfortunately, conventional techniques and other electronic-based platforms for exosome sensing are burdensome and inept for the POC distinction of aged blood factors. It is shown that EV-chip can quantitatively detect purified exosomes from plasma, with a limit of detection (LOD) of 2 × 104 particles mL-1 and a limit of quantification (LOQ) of 6 × 104 particles mL-1 . The sensitivity and compact electronics of the EV-chip improves upon previously published electronic biosensors, making it ideal for a physician's office or a simple biological laboratory. The sensitivity, selectivity, and portability of the EV-chip demonstrate the potential of the biosensor as a powerful point-of-care diagnostic and prognostic tool for age-related diseases.

We consider the use of extreme learning machines (ELM) for computational partial differential equations (PDE). In ELM the hidden-layer coefficients in the neural network are assigned to random values generated on $[-R_m,R_m]$ and fixed, where $R_m$ is a user-provided constant, and the output-layer coefficients are trained by a linear or nonlinear least squares computation. We present a method for computing the optimal value of $R_m$ based on the differential evolution algorithm. The presented method enables us to illuminate the characteristics of the optimal $R_m$ for two types of ELM configurations: (i) Single-Rm-ELM, in which a single $R_m$ is used for generating the random coefficients in all the hidden layers, and (ii) Multi-Rm-ELM, in which multiple $R_m$ constants are involved with each used for generating the random coefficients of a different hidden layer. We adopt the optimal $R_m$ from this method and also incorporate other improvements into the ELM implementation. In particular, here we compute all the differential operators involving the output fields of the last hidden layer by a forward-mode auto-differentiation, as opposed to the reverse-mode auto-differentiation in a previous work. These improvements significantly reduce the network training time and enhance the ELM performance. We systematically compare the computational performance of the current improved ELM with that of the finite element method (FEM), both the classical second-order FEM and the high-order FEM with Lagrange elements of higher degrees, for solving a number of linear and nonlinear PDEs. It is shown that the current improved ELM far outperforms the classical FEM. Its computational performance is comparable to that of the high-order FEM for smaller problem sizes, and for larger problem sizes the ELM markedly outperforms the high-order FEM., Comment: 46 pages, 35 figures

Background Cronobacter species are associated with severe foodborne infections in neonates and infants, with particular pathovars associated with specific clinical presentations. However, before 2008 the genus was regarded as a single species named Enterobacter sakazakii which was subdivided into 8 phenotypes. This study re-analyzed, using multi-locus sequence typing (MLST) and whole genome sequence with single nucleotide polymorphism analysis (WGS-SNP), 52 strains which had been identified as Enterobacter sakazakii as according to the convention at the time of isolation. These strains had been isolated from dairy product imports into China from 9 countries between 2005 and 6. Bioinformatic analysis was then used to analyze the relatedness and global dissemination of these strains. Result FusA allele sequencing revealed that 49/52 strains were Cronobacter sakazakii, while the remaining 3 strains were Escherichia coli, Enterobacter cloacae, and Franconibacter helveticus. The C. sakazakii strains comprised of 8 sequence types (STs) which included the neonatal pathovars ST1, ST4 and ST12. The predominant sequence type was ST13 (65.3%, 32/49) which had been isolated from dairy products imported from 6 countries. WGS-SNP analysis of the 32 C. sakazakii ST13 strains revealed 5 clusters and 5 unique strains which did not correlate with the country of product origin. Conclusion The mis-identification of E. coli, E. cloacae and F. helveticus as Cronobacter spp. reinforces the need to apply reliable methods to reduce the incidence of false positive and false negative results which may be of clinical significance. The WGS-SNP analysis demonstrated that indistinguishable Cronobacter strains within a sequence type can be unrelated, and may originate from multiple sources. The use of WGS-SNP analysis to distinguishing of strains within a sequence type has important relevance for tracing the source of outbreaks due to Cronobacter spp. Electronic supplementary material The online version of this article (10.1186/s12864-018-4881-9) contains supplementary material, which is available to authorized users.

Cronobacter sp., an opportunistic foodborne pathogen, can cause high mortality in neonatal and premature infants because this pathogen is associated with powdered infant formula (PIF) contamination. Biofilm formation is recognized as the most effective means to help Cronobacter survive throughout the long shelf-life of PIF, thus promoting resistance to cleaning agents and disinfectants. Crystal violet (CV) staining and fluorescence microscopy analyses were used to compare the biofilm formation ability among different Cronobacter strains, and then the weak biofilm former Cronobacter sakazakii ATCC 29544 and the strong biofilm former Cronobacter dubliniensis DSM 18707 were selected for further proteomic analysis. Two-dimensional liquid chromatography–tandem mass spectrometry, which was coupled with isobaric tags for relative and absolute quantification (iTRAQ) labeling, was employed to quantitatively identify the proteins that were differentially expressed in C. sakazakii ATCC 29544 compared to C. dubliniensis DSM 18707. In total, 1190 proteins were detected. Gene Ontology (GO) analysis indicated that these differentially expressed proteins are related to biological binding, cell structure, signal transduction, cell adhesion, and cellular interaction. Among these differential proteins, the expression levels of 177 non-redundant proteins were altered significantly by more than 5-fold, with 96 up-regulated proteins and 81 down-regulated. This study provides important information regarding the cellular requirements for the underlying mechanism of Cronobacter biofilm formation and its survival in harsh environments.

The main therapies of hepatocellular carcinoma (HCC) are hepatectomy and liver transplantation, but the recurrence rate of HCC after radical resection remains high. We established a novel method based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) for the rapid identification of four cancer stem cell-specific biomarkers to estimate the potential risk of HCC metastasis. After optimizing the final concentrations of Mg2+ and betaine, the sensitivity limits for detection of CK19 and EpCAM could reach 10 to 20 copies, while the sensitivity limits for the detection of CD133 and CD90 could reach 10 copies. We detected clinical specimens from 10 HCC patients and performed analysis before and after receiving hepatectomy using RT-LAMP and quantitative reverse transcription polymerase chain reaction (qRT-PCR). The results of both were consistent, but RT-LAMP was proved to be a more rapid, more sensitive, and more economic approach. This novel method is expected to estimate the recurrence and metastasis of HCC for clinical application by combining various low-cost circulating tumor cell sorting and detection tools.

Figure S1. Neighbour-joining phylogenetic tree derived from fusA gene sequences (438Â bp) for all isolates. (DOC 27Â kb)

Salmonella is the most common cause of bacterial food poisoning in humans worldwide. Thus, rapid and reliable methods for the detection of this pathogen are required. Real-time reverse-transcriptase polymerase chain reaction (rt-RT-PCR), which detects the presence of mRNA (shorter half-life than DNA) has shown great potential for detecting viable pathogens. We recently identified a few new potential specific DNA sequences for Salmonella enterica using a comparative genomics method (Chen et al., 2010). In the present study, we examined the expression of the Salmonella-specific sigDE operon (encoding invasion proteins within the pathogenicity island 5) under typical growth conditions to determine whether sigDE could be a useful viability marker for the bacterium. We then assayed sigDE mRNA from cells heat-treated at 60°C, 100°C, and 121°C (autoclaved), and found that mRNA was degraded in autoclaved bacterial samples. These results showed that the sigDE transcript is a suitable mRNA target for rt-RT-PCR with samples pretreated at 121°C. Thus, an rt-RT-PCR using sigDE primers was developed for the detection of viable Salmonella. An RNA internal amplification control was constructed by overlap extension PCR, synthesized using in vitro transcription with a T7 RNA polymerase promoter, and incorporated into the rt-RT-PCR system to eliminate false-negative results. The rt-RT-PCR system has the capability of specifically detecting all the tested S. enterica serovars, and the detection limit of this assay with cultures of Salmonella Typhimurium ATCC 13311 was 10(1) colony-forming units (CFU)/mL. After 18-h enrichment, sigDE-based rt-RT-PCR could detect as low as 10(0) CFU/mL of Salmonella from egg broth and milk.

The occurrence of outbreaks of Cronobacter strains causing necrotizing meningitis in China highlights the need for strain characterization and subtyping of this pathogenic species. A total of 43 Cronobacter isolates and five Enterobacteriaceae strains were used in this study. The strains were characterized using two molecular typing methods, including enterobacterial repetitive intergenic consensus sequence polymerase chain reaction (ERIC-PCR) and sequence analysis of the gyrB gene. Genetic profiles of cluster analysis from these two molecular typing tests clearly showed that there was no close relationship between Cronobacter spp. and Enterobacteriaceae strains. Discriminatory index of ERIC-PCR typing for the 43 Cronobacter isolates and five Enterobacteriaceae strains was high (D = 0.984) by Simpson's index of diversity based on the similarity value of more than 80% using BioNumerics version 5.0. Sequence analysis of the gyrB gene was proven to be suitable for the phylogenetic analysis of the Cronobacter strains. These results demonstrate that ERIC-PCR combined with sequence analysis of the gyrB gene may be a reliable, rapid typing strategy for Cronobacter strains. Practical Applications Molecular typing of foodborne pathogenic bacteria has been shown as a useful tool for tracking the source of infection and detection of virulent strains, as well as for determining the geographical and host distribution of possible variants. ERIC-PCR provides rapid clustered results when a large number of Cronobacter spp. isolates need to be subtyped rapidly. Furthermore, partial sequence analysis of the gyrB gene was utilized to differentiate among the closely related isolates. The results of the current study suggest that ERIC-PCR in conjunction with the gyrB sequence analysis would provide a reliable and accurate typing strategy for Cronobacter spp. strains. This combination of techniques can be used as a rapid means of comparing Cronobacter spp. isolates for epidemiological investigations.

The occurrence of outbreaks of Vibrio parahaemolyticus gastroenteritis in China highlights the need for strain characterization and subtyping of this pathogenic species. A total of 56 epidemiologically-unrelated strains of V. parahaemolyticus were isolated from clinical samples, seafood and various environmental sites in the middle-east coastline of China from 2006 to 2008. The isolates were characterized using four molecular typing methods, including ribotyping, enterobacterial repetitive intergenic consensus sequence PCR (ERIC-PCR), pulsed-field gel electrophoresis (PFGE), and sequence analysis of the gyrB gene. Genetic profiles of cluster analysis from these molecular typing tests clearly showed that there were differences in potential pathogenicity among isolates from seafood and its environments. Genetic characterization of two isolates (F13 and QS2) that originated from seafood demonstrated that they were potentially pathogenic. Discriminatory indices of four typing methods for the 56 V. parahaemolyticus isolates were differentiated by Simpson's Index of Diversity. The discriminatory index of ERIC-PCR typing was maximal (D=0.942), while that of sequence analysis of the gyrB gene was minimal (D=0.702). The discriminatory ability was greatly enhanced (D=0.966) when ERIC-PCR was coupled with sequence analysis of the gyrB gene. These results suggest that ERIC-PCR combined with sequence analysis of gyrB gene may be a reliable, rapid typing strategy for V. parahaemolyticus strains.

Enterobacter sakazakii is a gram-negative rod bacterium that was formerly known as “yellow-pigmented Enterobacter cloacae” until 1980. It is an emerging opportunistic pathogen associated with bacterial meningitis in immunocompromised neonates who ingested contaminated powdered infant formula. In several E. sakazakii-related outbreaks and sporadic cases, powdered infant formula was epidemiologically or microbiologically established as the source of infection. The International Commission on Microbiological Specifications for Foods has ranked E. sakazakii as a “severe hazard for restricted populations.” However, the organism was isolated at very low levels from commercial powdered infant formula and dry environmental samples collected from infant formula factories. In most cases, the contamination did not exceed 1 cfu per 100 g. Progress in understanding the epidemiology of E. sakazakii outbreaks and instituting effective control measures has been poor to date. To clarify the mechanisms involved in infectivity and enterotoxin production, we performed two-dimensional gel electrophoresis (2-DE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and isotope-coded affinity tags (ICATs)-LC -MS to identify and quantify differences in protein expression between the E. sakazakii strains. We found 23 spots in 2-DE and 37 proteins in ICAT analysis that were differentially expressed in E. sakazakii. These two methods gave us closely related but different information, suggesting that the two methods are complementary or at least supplementary. PRACTICAL APPLICATIONS Enterobacter sakazakii has been implicated in meningitis or enteritis with 20% to >50% mortality of infants who contract the disease. Our research has been used in verification of Enterobacter sakazakii isolated from infant formula and other milk and milk related foods. We have established standard maps of two Enterobacter sakazakii strains which were isolated from infant formula. Through appearance or absence of specific spots and their isoelectric point or molecular weight comparison, a two dimensional electrophoresis standard map can be developed and used as a powerful tool to differentiate Enterobacter sakazakii from other Enterobacteriaceae. This offers microbiologists powerful tools for Enterobacter sakazakii detection and provides more basic information to investigate the pathogenesis of Enterobacter sakazakii and contamination sources in infant formula production.

Cronobacter spp. has caused life-threatening neonatal infections mainly resulted from consumption of contaminated powdered infant formula. A total of 102 vegetable samples from retail markets were evaluated for the presence of Cronobacter spp. Thirty-five presumptive Cronobacter isolates were isolated and identified using API 20E and 16S rDNA sequencing analyses. All isolates and type strains were characterized using enterobacterial repetitive intergenic consensus sequence PCR (ERIC-PCR), and genetic profiles of cluster analysis from this molecular typing test clearly showed that there were differences among isolates from different vegetables. A polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) based on the amplification of the gyrB gene (1258 bp) was developed to differentiate among Cronobacter species. A new PCR-RFLP assay based on the amplification of the gyrB gene using Alu I and Hinf I endonuclease combination is established and it has been confirmed an accurate and rapid subtyping method to differentiate Cronobacter species. Sequence analysis of the gyrB gene was proven to be suitable for the phylogenetic analysis of the Cronobacter strains, which has much better resolution based on SNPs in the identification of Cronobacter species specificity than PCR-RFLP and ERIC-PCR. Our study further confirmed that vegetables are one of the most common habitats or sources of Cronobacter spp. contamination in the middle-east coastline of China.

In this project, a highly precise quantitative method based on the digital polymerase chain reaction (dPCR) technique was developed to determine the weight of pork and chicken in meat products. Real-time quantitative polymerase chain reaction (qPCR) is currently used for quantitative molecular analysis of the presence of species-specific DNAs in meat products. However, it is limited in amplification efficiency and relies on standard curves based Ct values, detecting and quantifying low copy number target DNA, as in some complex mixture meat products. By using the dPCR method, we find the relationships between the raw meat weight and DNA weight and between the DNA weight and DNA copy number were both close to linear. This enabled us to establish formulae to calculate the raw meat weight based on the DNA copy number. The accuracy and applicability of this method were tested and verified using samples of pork and chicken powder mixed in known proportions. Quantitative analysis indicated that dPCR is highly precise in quantifying pork and chicken in meat products and therefore has the potential to be used in routine analysis by government regulators and quality control departments of commercial food and feed enterprises.

The occurrence of outbreaks of necrotizing meningitis caused by Cronobacter spp. in neonates highlights the need for rapid detection and accurate identification of this pathogenic species. The gold standard for isolation and identification of Cronobacter spp. from powdered infant formula is time consuming and labor intensive. The gyrB gene that encodes the B subunit of DNA gyrase (topoisomerase type II) was found to be suitable for the identification of Cronobacter spp. A region of the gyrB gene of 38 Cronobacter spp. strains and 5 Enterobacter spp. strains was amplified and sequenced, and a pair of primers was designed and synthesized based on the sequence of the gyrB gene. A polymerase chain reaction (PCR) system was developed and optimized to detect Cronobacter spp. The PCR assay amplified a 438 bp DNA product from all 38 Cronobacter spp. strains tested but not from 34 other bacteria. The detection limit was 1.41 pg/PCR (equivalent 282 genomic copies) when the genomic DNA of Cronobacter sakazakii ATCC 29544 was 10-fold diluted. Infant formula powders from 3 different commercial brands were inoculated with strains ATCC 29544 at a level of 56 colony-forming units, and the target fragment were produced after samples were enriched for 6 h at 37 °C. Twenty-five food samples were evaluated by the PCR assay and the conventional method. A PCR product of the expected size was obtained from 3 samples; however, Cronobacter spp. strains were isolated from only 2 samples by the conventional method. This method is a useful tool for rapid identification of Cronobacter spp. in food and potentially environmental samples.

Background To date, over 150 genetically modified (GM) crops are widely cultivated. To comply with regulations developed for genetically modified organisms (GMOs), including labeling policies, many detection methods for GMO identification and quantification have been developed. Results To detect the entrance and exit of unauthorized GM crop events in China, we developed a novel quadruplex real-time PCR method for simultaneous detection and quantification of GM cotton events GHB119 and T304-40 in cotton-derived products (based on the 5′-flanking sequence) and the insect-resistance gene Cry2Ae. The limit of detection was 10 copies for GHB119 and Cry2Ae and 25 copies for T304-40. The limit of quantification was 25 copies for GHB119 and Cry2Ae and 50 copies for T304-40. Moreover, low bias and acceptable standard deviation and relative standard deviation values were obtained in quantification analysis of six blind samples containing different GHB119 and T304-40 ingredients. Conclusions The developed quadruplex quantitative method could be used for quantitative detection of two GM cotton events (GHB119 and T304-40) and Cry2Ae gene ingredient in cotton derived products.

Cronobacterspp. is a conditioned pathogen found mainly in milk powder; it can seriously harm infant health. We investigated biofilm formation in eight strains ofCronobacterspp. and found that DSM 18707 had the strongest capacity to form biofilm. Biofilm-related genesbcsA,bcsG,flgJ, andflhEwere selected for qRT-PCR detection. Expression ofbcsGinCronobacterspp. was associated with the ability to form biofilm. Knockout ofbcsGin DSM 18707 was associated with markedly reduced biofilm formation and exopolysaccharide content relative to the wild type. Moreover, fluorescence microscopy revealed that the knockout mutants had comparatively lower biofilm density. In the knockout mutants,bcsA,flgJ, andflhEwere up-regulated in the first three days but down-regulated by days 4 and 5. Hence, the expression levels of bacterial biofilm-related genes may change with biofilm production; moreover,bcsGpositively regulates the formation of exopolysaccharides and biofilm inCronobacterspp.