Enteroaggregative Escherichia coli in mid-Norway: A prospective, case control study.

BACKGROUND: The use of molecular methods has led to increased detection of Enteroaggregative Escherichia coli (EAEC) in faecal samples. Studies have yielded conflicting results regarding the clinical relevance of this finding. The objective of this study was to investigate the prevalence of EAEC in faecal samples from patients with diarrhoea and healthy controls and describe characteristics of EAEC positive persons. METHODS: From March 1st, 2017 to February 28th, 2019, we investigated all consecutive faecal samples from patients with diarrhoea received at the laboratory and collected faecal samples from randomly invited healthy controls from mid-Norway. Real-time multiplex PCR was used for detection of bacterial, viral, and parasitic pathogens. We registered sex, age, urban versus non-urban residency, and travel history for all participants. Statistical analyses were performed with Pearson chi-squared test, Kruskal-Wallis test, and Mann-Whitney U test. RESULTS: We identified EAEC in 440 of 9487 (4.6%) patients with diarrhoea and 8 of 375 (2.2%) healthy controls. The EAEC prevalence was 19.1% among those with diarrhoea and recent foreign travel and 2.2% in those without travel history independent of diarrhoea. Concomitant pathogens were detected in 64.3% of EAEC-positive patients with diarrhoea. The median age was 28.5 in those with EAEC-positive diarrhoea and 38 in those with EAEC-negative diarrhoea (p <0.01). In patients with diarrhoea, travel was reported in 72% of those with EAEC and concomitant pathogens, and 54% and 12% in those with only EAEC and no EAEC, respectively (p <0.01). CONCLUSIONS: EAEC was a common detection, particularly in patients with diarrhoea and recent international travel, and was found together with other intestinal pathogens in the majority of cases. Our results suggest that domestically acquired EAEC is not associated with diarrhoea. Patients with EAEC-positive diarrhoea and concomitant pathogens were young and often reported recent travel history compared to other patients with diarrhoea.

Joint changes in RNA, RNA polymerase II, and promoter activity through the cell cycle identify non-coding RNAs involved in proliferation.

Proper regulation of the cell cycle is necessary for normal growth and development of all organisms. Conversely, altered cell cycle regulation often underlies proliferative diseases such as cancer. Long non-coding RNAs (lncRNAs) are recognized as important regulators of gene expression and are often found dysregulated in diseases, including cancers. However, identifying lncRNAs with cell cycle functions is challenging due to their often low and cell-type specific expression. We present a highly effective method that analyses changes in promoter activity, transcription, and RNA levels for identifying genes enriched for cell cycle functions. Specifically, by combining RNA sequencing with ChIP sequencing through the cell cycle of synchronized human keratinocytes, we identified 1009 genes with cell cycle-dependent expression and correlated changes in RNA polymerase II occupancy or promoter activity as measured by histone 3 lysine 4 trimethylation (H3K4me3). These genes were highly enriched for genes with known cell cycle functions and included 57 lncRNAs. We selected four of these lncRNAs-SNHG26, EMSLR, ZFAS1, and EPB41L4A-AS1-for further experimental validation and found that knockdown of each of the four lncRNAs affected cell cycle phase distributions and reduced proliferation in multiple cell lines. These results show that many genes with cell cycle functions have concomitant cell-cycle dependent changes in promoter activity, transcription, and RNA levels and support that our multi-omics method is well suited for identifying lncRNAs involved in the cell cycle.

Single Cell Transcriptomic and Chromatin Profiles Suggest Layer Vb Is the Only Layer With Shared Excitatory Cell Types in the Medial and Lateral Entorhinal Cortex.

All brain functionality arises from the activity in neural circuits in different anatomical regions. These regions contain different circuits comprising unique cell types. An integral part to understanding neural circuits is a full census of the constituent parts, i.e., the neural cell types. This census can be based on different characteristics. Previously combinations of morphology and physiology, gene expression, and chromatin accessibility have been used in various cortical and subcortical regions. This has given an extensive yet incomplete overview of neural cell types. However, these techniques have not been applied to all brain regions. Here we apply single cell analysis of accessible chromatin on two similar but different cortical regions, the medial and the lateral entorhinal cortices. Even though these two regions are anatomically similar, their intrinsic and extrinsic connectivity are different. In 4,136 cells we identify 20 different clusters representing different cell types. As expected, excitatory cells show regionally specific clusters, whereas inhibitory neurons are shared between regions. We find that several deep layer excitatory neuronal cell types as defined by chromatin profile are also shared between the two different regions. Integration with a larger scRNA-seq dataset maintains this shared characteristic for cells in Layer Vb. Interestingly, this layer contains three clusters, two specific to either subregion and one shared between the two. These clusters can be putatively associated with particular functional and anatomical cell types found in this layer. This information is a step forwards into elucidating the cell types within the entorhinal circuit and by extension its functional underpinnings.