Subversion of actin dynamics by EspM effectors of attaching and effacing bacterial pathogens

Rho GTPases are common targets of bacterial toxins and type III secretion system effectors. IpgB1 and IpgB2 of Shigella and Map of enteropathogenic (EPEC) and enterohemorrhagic (EHEC) Escherichia coli were recently grouped together on the basis that they share a conserved WxxxE motif. In this study, we characterized six WxxxE effectors from attaching and effacing pathogens: TrcA and EspM1 of EPEC strain B171, EspM1 and EspM2 of EHEC strain Sakai and EspM2 and EspM3 of Citrobacter rodentium. We show that EspM2 triggers formation of global parallel stress fibres, TrcA and EspM1 induce formation of localized parallel stress fibres and EspM3 triggers formation of localized radial stress fibres. Using EspM2 and EspM3 as model effectors, we report that while substituting the conserved Trp with Ala abolished activity, conservative Trp to Tyr or Glu to Asp substitutions did not affect stress-fibre formation. We show, using dominant negative constructs and chemical inhibitors, that the activity of EspM2 and EspM3 is RhoA and ROCK-dependent. Using Rhotekin pull-downs, we have shown that EspM2 and EspM3 activate RhoA; translocation of EspM2 and EspM3 triggered phosphorylation of cofilin. These results suggest that the EspM effectors modulate actin dynamics by activating the RhoA signalling pathway

Frontotemporal dementia caused by CHMP2B mutation is characterised by neuronal lysosomal storage pathology

Mutations in the charged multivesicular body protein 2B (CHMP2B) cause frontotemporal dementia (FTD). We report that mice which express FTD-causative mutant CHMP2B at physiological levels develop a novel lysosomal storage pathology characterised by large neuronal autofluorescent aggregates. The aggregates are an early and progressive pathology that occur at 3 months of age and increase in both size and number over time. These autofluorescent aggregates are not observed in mice expressing wild-type CHMP2B, or in non-transgenic controls, indicating that they are a specific pathology caused by mutant CHMP2B. Ultrastructural analysis and immuno- gold labelling confirmed that they are derived from the endolysosomal system. Consistent with these findings, CHMP2B mutation patient brains contain morphologically similar autofluorescent aggregates. These aggregates occur significantly more frequently in human CHMP2B mutation brain than in neurodegenerative disease or age-matched control brains. These data suggest that lysosomal storage pathology is the major neuronal pathology in FTD caused by CHMP2B mutation. Recent evidence suggests that two other genes associated with FTD, GRN and TMEM106B are important for lysosomal function. Our identification of lysosomal storage pathology in FTD caused by CHMP2B mutation now provides evidence that endolysosomal dysfunction is a major degenerative pathway in FTD

Classes of Multiple Decision Functions Strongly Controlling FWER and FDR

This paper provides two general classes of multiple decision functions where each member of the first class strongly controls the family-wise error rate (FWER), while each member of the second class strongly controls the false discovery rate (FDR). These classes offer the possibility that an optimal multiple decision function with respect to a pre-specified criterion, such as the missed discovery rate (MDR), could be found within these classes. Such multiple decision functions can be utilized in multiple testing, specifically, but not limited to, the analysis of high-dimensional microarray data sets.Comment: 19 page

Do Natural Proteins Differ from Random Sequences Polypeptides? Natural vs. Random Proteins Classification Using an Evolutionary Neural Network

Are extant proteins the exquisite result of natural selection or are they random sequences slightly edited by evolution? This question has puzzled biochemists for long time and several groups have addressed this issue comparing natural protein sequences to completely random ones coming to contradicting conclusions. Previous works in literature focused on the analysis of primary structure in an attempt to identify possible signature of evolutionary editing. Conversely, in this work we compare a set of 762 natural proteins with an average length of 70 amino acids and an equal number of completely random ones of comparable length on the basis of their structural features. We use an ad hoc Evolutionary Neural Network Algorithm (ENNA) in order to assess whether and to what extent natural proteins are edited from random polypeptides employing 11 different structure-related variables (i.e. net charge, volume, surface area, coil, alpha helix, beta sheet, percentage of coil, percentage of alpha helix, percentage of beta sheet, percentage of secondary structure and surface hydrophobicity). The ENNA algorithm is capable to correctly distinguish natural proteins from random ones with an accuracy of 94.36%. Furthermore, we study the structural features of 32 random polypeptides misclassified as natural ones to unveil any structural similarity to natural proteins. Results show that random proteins misclassified by the ENNA algorithm exhibit a significant fold similarity to portions or subdomains of extant proteins at atomic resolution. Altogether, our results suggest that natural proteins are significantly edited from random polypeptides and evolutionary editing can be readily detected analyzing structural features. Furthermore, we also show that the ENNA, employing simple structural descriptors, can predict whether a protein chain is natural or random

A rare case of repeated anastomotic recurrence due to tumor implantation after curative surgery for sigmoid colon cancer

<p>Abstract</p> <p>Background</p> <p>Anastomotic recurrence is often experienced at colocolic or colorectal anastomoses. Tumor cell implantation has been reported as the mechanism of anastomotic recurrence. However, anastomotic recurrence occurring repeatedly after curative surgery is rare. We herein report a rare case of repeated anastomotic recurrence after curative surgery for sigmoid colon cancer.</p> <p>Case presentation</p> <p>A 51-year-old man underwent radical surgery for sigmoid colon cancer. However, anastomotic recurrence developed three times during three years and six months after the initial operation in spite of irrigation with 5% povidone-iodine before anastomosis. The serum carcinoembryonic antigen (CEA) level had been within normal limits after sigmoidectomy. Finally, the patient underwent abdominoperineal resection. The clinico-pathological findings revealed that possible tumor cell implantation caused these anastomotic recurrences. The patients survived without recurrence during the follow-up period of seven years and nine months.</p> <p>Conclusion</p> <p>We experienced a rare case of repeated anastomotic recurrence due to possible tumor implantation after curative surgery for sigmoid colon cancer; however the prognosis was ultimately very good. CEA monitoring was insensitive for detection of anastomotic recurrence in this case.</p

Empowerment or Engagement? Digital Health Technologies for Mental Healthcare

We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare

Mapping of Mycobacterium tuberculosis Complex Genetic Diversity Profiles in Tanzania and Other African Countries

The aim of this study was to assess and characterize Mycobacterium tuberculosis complex (MTBC) genotypic diversity in Tanzania, as well as in neighbouring East and other several African countries. We used spoligotyping to identify a total of 293 M. tuberculosis clinical isolates (one isolate per patient) collected in the Bunda, Dar es Salaam, Ngorongoro and Serengeti areas in Tanzania. The results were compared with results in the SITVIT2 international database of the Pasteur Institute of Guadeloupe. Genotyping and phylogeographical analyses highlighted the predominance of the CAS, T, EAI, and LAM MTBC lineages in Tanzania. The three most frequent Spoligotype International Types (SITs) were: SIT21/CAS1-Kili (n = 76; 25.94%), SIT59/LAM11-ZWE (n = 22; 7.51%), and SIT126/EAI5 tentatively reclassified as EAI3-TZA (n = 18; 6.14%). Furthermore, three SITs were newly created in this study (SIT4056/EAI5 n = 2, SIT4057/T1 n = 1, and SIT4058/EAI5 n = 1). We noted that the East-African-Indian (EAI) lineage was more predominant in Bunda, the Manu lineage was more common among strains isolated in Ngorongoro, and the Central-Asian (CAS) lineage was more predominant in Dar es Salaam (p-value<0.0001). No statistically significant differences were noted when comparing HIV status of patients vs. major lineages (p-value = 0.103). However, when grouping lineages as Principal Genetic Groups (PGG), we noticed that PGG2/3 group (Haarlem, LAM, S, T, and X) was more associated with HIV-positive patients as compared to PGG1 group (Beijing, CAS, EAI, and Manu) (p-value = 0.03). This study provided mapping of MTBC genetic diversity in Tanzania (containing information on isolates from different cities) and neighbouring East African and other several African countries highlighting differences as regards to MTBC genotypic distribution between Tanzania and other African countries. This work also allowed underlining of spoligotyping patterns tentatively grouped within the newly designated EAI3-TZA lineage (remarkable by absence of spacers 2 and 3, and represented by SIT126) which seems to be specific to Tanzania. However, further genotyping information would be needed to confirm this specificity