A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns

Changes in the microbiota from fresh to spoiled meat, determined by culture and 16S rRNA analysis

Growth of meat microbiota usually results in spoilage of meat that can be perceived by consumers due to sensory changes. However, a high bacterial load does not necessarily result in sensory deviation of meat; nevertheless, this meat is considered unfit for human consumption. Therefore, the aims of this study were to investigate changes in the microbiota from fresh to spoiled meat and whether the proportions of certain bacteria can probably be used to indicate the hygiene status of meat. For this purpose, 12 fresh pork samples were divided into two groups, and simultaneously aerobically stored at 4°C and 22°C. At each time-temperature point (fresh meat, days 6, 13, and 20 at 4°C, and days 1, 2, 3, and 6 at 22°C), 12 meat subsamples were investigated. Sequences obtained from next-generation sequencing (NGS) were further analyzed down to species level. Plate counting of six bacterial groups and NGS results showed that Pseudomonas spp. and lactic acid bacteria (LAB) were found in a high proportion in all stored meat samples and can therefore be considered as important "spoilage indicator bacteria". On the contrary, sequences belonging to Staphylococcus epidermidis were found in a relatively high proportion in almost all fresh meat samples but were less common in stored meat. In this context, they can be considered as "hygiene indicator bacteria" of meat. Based on these findings, the proportion of the "hygiene indicator bacteria" in relation to the "spoilage indicator bacteria" was calculated to determine a "hygiene index" of meat. This index has a moderate to strong correlation to bacterial loads obtained from culture (p < 0.05), specifically to Pseudomonas spp., LAB and total viable counts (TVCs). Knowledge of the proportions of hygiene and spoilage indicator bacteria obtained by NGS could help to determine the hygiene status even of (heat-) processed composite meat products for the first time, thus enhancing food quality assurance and consumer protection

Associative Formal Power Series in Two Indeterminates

Investigating the associativity equation for formal power series in two variables we show that the transcendental associative formal power series are of order one or two and that they can be represented by an invertible formal power series in one variable. We also discuss the convergence of associative formal power series

Viable Campylobacter jejuni on eggshells and its potential to cross-contaminate egg white and yolk when using a manual separation technique, determined by culture and propidium monoazide (PMA) qPCR

Manual separation of egg yolk from egg white using the eggshell is common practice in private households. For this, the egg is cracked and both components are separated by passing the egg yolk back and forth between the two halves of the eggshell, allowing the egg white to drip down while the egg yolk remains in the shell. During this process, the egg content naturally gets in contact with the outside of the eggshell, which might lead to a cross-contamination with its microorganisms, thus was correspondingly assessed in this study. Campylobacter jejuni is one of the most important zoonotic pathogens that can be found on eggshells. Therefore, this bacterium was used to artificially contaminate the eggshells (n = 22) with concentrations of 3.1 ± 0.6 log10 cfu/g. After separating the egg yolk from the egg white, cross-contamination was determined using culture and qPCR. Altogether, cross-contaminations with C. jejuni were found in 15 egg white (68%) and in three egg yolk (14%) samples. Afterward, 90 eggs from 30 egg packs from different producers in and around Munich (Germany) were obtained for field study purposes. To address the problem of culturing due to a possible viable but nonculturable (VBNC) status of C. jejuni, a method to differentiate viable and dead C. jejuni on eggshell using 10 µM propidium monoazide (PMA) and qPCR was developed. As a result, seven egg packs (23%) were positive for C. jejuni. Of these, only one (3%) was contaminated with viable cells, but still in a concentration of 3.3 log10 cells/g shell. According to these results and considering that eggshells might also be naturally contaminated with other pathogens, the authors recommend avoiding the manual separation technique of egg white and yolk by the eggshell. Especially if raw egg white or yolk is used for preparation of not sufficiently heated foods, where contaminating pathogens are not inactivated during processing, this technique might be a safety hazard for the consumer

Quantitative cardiovascular magnetic resonance: extracellular volume, native T1 and 18F-FDG PET/CMR imaging in patients after revascularized myocardial infarction and association with markers of myocardial damage and systemic inflammation

Abstract Background Characterization of tissue integrity and inflammatory processes after acute myocardial infarction (AMI) using non-invasive imaging is predictive of patient outcome. Quantitative cardiovascular magnetic resonance (CMR) techniques such as native T1 and extracellular volume (ECV) mapping as well as 18F-FDG positron emission tomography (PET) imaging targeting inflammatory cell populations are gaining acceptance, but are often applied without assessing their quantitative potential. Using simultaneously acquired PET/CMR data from patients early after AMI, this study quantitatively compares these three imaging markers and investigates links to blood markers of myocardial injury and systemic inflammatory activity. Methods A total of 25 patients without microvascular obstruction were retrospectively recruited. All imaging was simultaneously performed 5 ± 1 days after revascularization following AMI on an integrated 3T PET/MRI scanner. Native and post-contrast T1 data were acquired using a modified Look-Locker inversion recovery (MOLLI) sequence, ECV maps were calculated using individually sampled hematocrit. 18F-FDG PET was executed after 1 day of dietary preparation, 12 h of fasting, and administration of heparin. ECV, 18F-FDG and native T1 data were compared mutually as well as to peak counts of peripheral blood markers (creatine kinase, creatine kinase-MB, troponin, leukocytes, monocytes) and infarct size. Results High intra-patient correlations of relative ECV, 18F-FDG PET and native T1 signal increases were observed in combination with no inter-patient correlation of maximum absolute values at the infarct center, suggesting well-colocalized but physiologically diverse processes begetting the respective image signals. Comparison of maximum image signals to markers of myocardial damage and systemic inflammation yielded highly significant correlations of ECV to peak creatine kinase-MB and overall infarct size as well as between native T1 and peak monocyte counts. Conclusions Absolute native T1 values at the infarct core early after AMI can be linked to the systemic inflammatory response independent of infarct size. Absolute ECV at the infarct core is related to both infarct size and blood markers of myocardial damage