An improved bind-n-seq strategy to determine protein-DNA interactions validated using the bacterial transcriptional regulator YipR.

BACKGROUND: Interactions between transcription factors and DNA lie at the centre of many biological processes including DNA recombination, replication, repair and transcription. Most bacteria encode diverse proteins that act as transcription factors to regulate various traits. Several technologies for identifying protein-DNA interactions at the genomic level have been developed. Bind-n-seq is a high-throughput in vitro method first deployed to analyse DNA interactions associated with eukaryotic zinc-finger proteins. The method has three steps (i) binding protein to a randomised oligonucleotide DNA target library, (ii) deep sequencing of bound oligonucleotides, and (iii) a computational algorithm to define motifs among the sequences. The classical Bind-n-seq strategy suffers from several limitations including a lengthy wet laboratory protocol and a computational algorithm that is difficult to use. We introduce here an improved, rapid, and simplified Bind-n-seq protocol coupled with a user-friendly downstream data analysis and handling algorithm, which has been optimized for bacterial target proteins. We validate this new protocol by showing the successful characterisation of the DNA-binding specificities of YipR (YajQ interacting protein regulator), a well-known transcriptional regulator of virulence genes in the bacterial phytopathogen Xanthomonas campestris pv. campestris (Xcc). RESULTS: The improved Bind-n-seq approach identified several DNA binding motif sequences for YipR, in particular the CCCTCTC motif, which were located in the promoter regions of 1320 Xcc genes. Informatics analysis revealed that many of these genes regulate functions associated with virulence, motility, and biofilm formation and included genes previously found involved in virulence. Additionally, electromobility shift assays show that YipR binds to the promoter region of XC_2633 in a CCCTCTC motif-dependent manner. CONCLUSION: We present a new and rapid Bind-n-seq protocol that should be useful to investigate DNA-binding proteins in bacteria. The analysis of YipR DNA binding using this protocol identifies a novel DNA sequence motif in the promoter regions of target genes that define the YipR regulon.

Targeting of cathepsin S reduces cystic fibrosis-like lung disease.

Cathepsin S (CatS) is upregulated in the lungs of patients with cystic fibrosis (CF). However, its role in CF lung disease pathogenesis remains unclear.In this study, ß-epithelial Na+ channel-overexpressing transgenic (ßENaC-Tg) mice, a model of CF-like lung disease, were crossed with CatS null (CatS-/-) mice or treated with the CatS inhibitor VBY-999.Levels of active CatS were elevated in the lungs of ßENaC-Tg mice compared with wild-type (WT) littermates. CatS-/-ßENaC-Tg mice exhibited decreased pulmonary inflammation, mucus obstruction and structural lung damage compared with ßENaC-Tg mice. Pharmacological inhibition of CatS resulted in a significant decrease in pulmonary inflammation, lung damage and mucus plugging in the lungs of ßENaC-Tg mice. In addition, instillation of CatS into the lungs of WT mice resulted in inflammation, lung remodelling and upregulation of mucin expression. Inhibition of the CatS target, protease-activated receptor 2 (PAR2), in ßENaC-Tg mice resulted in a reduction in airway inflammation and mucin expression, indicating a role for this receptor in CatS-induced lung pathology.Our data indicate an important role for CatS in the pathogenesis of CF-like lung disease mediated in part by PAR2 and highlight CatS as a therapeutic target.

Time dependent expression of the blood biomarkers EIF2D and TOX in patients with schizophrenia.

BACKGROUND: During last years, there has been an intensive search for blood biomarkers in schizophrenia to assist in diagnosis, prognosis and clinical management of the disease. METHODS: In this study, we first conducted a weighted gene coexpression network analysis to address differentially expressed genes in peripheral blood from patients with chronic schizophrenia (n = 30) and healthy controls (n = 15). The discriminating performance of the candidate genes was further tested in an independent cohort of patients with first-episode schizophrenia (n = 124) and healthy controls (n = 54), and in postmortem brain samples (cingulate and prefrontal cortices) from patients with schizophrenia (n = 34) and healthy controls (n = 35). RESULTS: The expression of the Eukaryotic Translation Initiation Factor 2D (EIF2D) gene, which is involved in protein synthesis regulation, was increased in the chronic patients of schizophrenia. On the contrary, the expression of the Thymocyte Selection-Associated High Mobility Group Box (TOX) gene, involved in immune function, was reduced. EIF2D expression was also altered in first-episode schizophrenia patients, but showing reduced levels. Any of the postmortem brain areas studied did not show differences of expression of both genes. CONCLUSIONS: EIF2D and TOX are putative blood markers of chronic patients of schizophrenia, which expression change from the onset to the chronic disease, unraveling new biological pathways that can be used for the development of new intervention strategies in the diagnosis and prognosis of schizophrenia disease.

Comment on 'Discovering hospital admission patterns using models learnt from electronic hospital records'. The importance of using the right codes.

CONTACT: guillermo.lopez@unimelb.edu.au.

Patient-reported outcomes and therapeutic affordances of social media: findings from a global online survey of people with chronic pain.

BACKGROUND: Patient-reported outcomes (PROs) from social media use in chronic disease management continue to emerge. While many published articles suggest the potential for social media is positive, there is a lack of robust examination into mediating mechanisms that might help explain social media's therapeutic value. This study presents findings from a global online survey of people with chronic pain (PWCP) to better understand how they use social media as part of self-management. OBJECTIVE: Our aim is to improve understanding of the various health outcomes reported by PWCP by paying close attention to therapeutic affordances of social media. We wish to examine if demographics of participants underpin health outcomes and whether the concept of therapeutic affordances explains links between social media use and PROs. The goal is for this to help tailor future recommendations for use of social media to meet individuals' health needs and improve clinical practice of social media use. METHODS: A total of 231 PWCP took part in a global online survey investigating PROs from social media use. Recruited through various chronic disease entities and social networks, participants provided information on demographics, health/pain status, social media use, therapeutic affordances, and PROs from use. Quantitative analysis was performed on the data using descriptive statistics, cross-tabulation, and cluster analysis. RESULTS: The total dataset represented 218 completed surveys. The majority of participants were university educated (67.0%, 146/218) and female (83.9%, 183/218). More than half (58.7%, 128/218) were married/partnered and not working for pay (75.9%, 88/116 of these due to ill health). Fibromyalgia (46.6%, 55/118) and arthritis (27.1%, 32/118) were the most commonly reported conditions causing pain. Participants showed a clear affinity for social network site use (90.0%, 189/210), followed by discussion forums and blogs. PROs were consistent, suggesting that social media positively impact psychological, social, and cognitive health. Analysis also highlighted two strong correlations linking platform used and health outcomes (particularly psychological, social, and cognitive) to (1) the narrative affordance of social media and (2) frequency of use of the platforms. CONCLUSIONS: Results did not uncover definitive demographics or characteristics of PWCP for which health outcomes are impacted. However, findings corroborate literature within this domain suggesting that there is a typical profile of people who use social media for health and that social media are more suited to particular health outcomes. Exploration of the relationship between social media's therapeutic affordances and health outcomes, in particular the narration affordance, warrants further attention by patients and clinicians.

The presence of HIV-1 Tat protein second exon delays fas protein-mediated apoptosis in CD4+ T lymphocytes: a potential mechanism for persistent viral production.

HIV-1 replication is efficiently controlled by the regulator protein Tat (101 amino acids) and codified by two exons, although the first exon (1-72 amino acids) is sufficient for this process. Tat can be released to the extracellular medium, acting as a soluble pro-apoptotic factor in neighboring cells. However, HIV-1-infected CD4(+) T lymphocytes show a higher resistance to apoptosis. We observed that the intracellular expression of Tat delayed FasL-mediated apoptosis in both peripheral blood lymphocytes and Jurkat cells, as it is an essential pathway to control T cell homeostasis during immune activation. Jurkat-Tat cells showed impairment in the activation of caspase-8, deficient release of mitochondrial cytochrome c, and delayed activation of both caspase-9 and -3. This protection was due to a profound deregulation of proteins that stabilized the mitochondrial membrane integrity, such as heat shock proteins, prohibitin, or nucleophosmin, as well as to the up-regulation of NF-κB-dependent anti-apoptotic proteins, such as BCL2, c-FLIPS, XIAP, and C-IAP2. These effects were observed in Jurkat expressing full-length Tat (Jurkat-Tat101) but not in Jurkat expressing the first exon of Tat (Jurkat-Tat72), proving that the second exon, and particularly the NF-κB-related motif ESKKKVE, was necessary for Tat-mediated protection against FasL apoptosis. Accordingly, the protection exerted by Tat was independent of its function as a regulator of both viral transcription and elongation. Moreover, these data proved that HIV-1 could have developed strategies to delay FasL-mediated apoptosis in infected CD4(+) T lymphocytes through the expression of Tat, thus favoring the persistent replication of HIV-1 in infected T cells.

Digital Interventions and Their Unexpected Outcomes - Time for Digitalovigilance?

The application of digital interventions in healthcare beyond research has been translated in the development of software as a medical device. Along with corresponding regulations for medical devices, there is a need for assessing adverse events to conduct post-market surveillance and to appropriately label digital health interventions to ensure proper use and patient safety. To date unexpected consequences of digital health interventions are neglected or ignored, or at least remain undescribed in literature. This paper is intended to raise awareness across the research community about these upcoming challenges. We recommend that - together with developing a new research field of digitalovigilance - a systematic assessment and monitoring of adverse events and unexpected interactions be included in clinical trials, along with the reporting of such events and the conduct of meta-analyses on critical aspects.

A Text Mining Approach to Explore IFNε Literature and Biological Mechanisms.

Interferons (IFN) constitute a primary line of protection against mucosal infection, with IFN research spanning over 60 years and encompassing a vast ever-expanding amount of literature. Most of what is currently understood has been derived from extensive research defining the roles of "classical" type I IFNs, IFNα and IFNß. However, little is known regarding responses elicited by less well-characterized IFN subtypes such as IFNε. In this paper, we combined a deductive text mining analysis of IFNε literature characterizing literature-derived knowledge with a comparative analysis of other type I and type III IFNs. Utilizing these approaches, three clusters of terms were extracted from the literature covering different aspects of IFNε research and a set of 47 genes uniquely cited in the context of IFNε. The use of these "in silico" approaches support the expansion of current understanding and the creation of new knowledge surrounding IFNε.

Assessing the Potential Risks of Digital Therapeutics (DTX): The DTX Risk Assessment Canvas.

MOTIVATION: Digital therapeutics (DTX), i.e., health interventions that are provided through digital means, are increasingly available for use; in some countries, physicians can even prescribe selected DTX following a reimbursement by health insurances. This results in an increasing need for methodologies to consider and monitor DTX's negative consequences, their risks to patient safety, and possible adverse events. However, it is completely unknown which aspects should be subject to surveillance given the missing experiences with the tools and their negative impacts. OBJECTIVE: Our aim is to develop a tool-the DTX Risk Assessment Canvas-that enables researchers, developers, and practitioners to reflect on the negative consequences of DTX in a participatory process. METHOD: Taking the well-established business model canvas as a starting point, we identified relevant aspects to be considered in a risk assessment of a DTX. The aspects or building blocks of the canvas were constructed in a two-way process: first, we defined the aspects relevant for discussing and reflecting on how a DTX might bring negative consequences and risks for its users by considering ISO/TS 82304-2, the scientific literature, and by reviewing existing DTX and their listed adverse effects. The resulting aspects were grouped into thematic blocks and the canvas was created. Second, six experts in health informatics and mental health provided feedback and tested the understandability of the initial canvas by individually applying it to a DTX of their choice. Based on their feedback, the canvas was modified. RESULTS: The DTX Risk Assessment Canvas is organized into 15 thematic blocks which are in turn grouped into three thematic groups considering the DTX itself, the users of the DTX, and the effects of the DTX. For each thematic block, questions have been formulated to guide the user of the canvas in reflecting on the single aspects. Conclusions: The DTX Risk Assessment Canvas is a tool to reflect the negative consequences and risks of a DTX by discussing different thematic blocks that together constitute a comprehensive interpretation of a DTX regarding possible risks. Applied during the DTX design and development phase, it can help in implementing countermeasures for mitigation or means for their monitoring.

Modelling the Gastrointestinal Carriage of Klebsiella pneumoniae Infections.

Klebsiella pneumoniae is a leading cause of nosocomial and community acquired infections, making K. pneumoniae the pathogen that is associated with the second largest number of deaths attributed to any antibiotic resistant infection. K. pneumoniae colonizes the nasopharynx and the gastrointestinal tract in an asymptomatic manner without dissemination to other tissues. Importantly, gastrointestinal colonization is a requisite for infection. Our understanding of K. pneumoniae colonization is still based on interrogating mouse models in which animals are pretreated with antibiotics to disturb the colonization resistance imposed by the gut microbiome. In these models, infections disseminate to other tissues. Here, we report a murine model to allow for the study of the gastrointestinal colonization of K. pneumoniae without tissue dissemination. Hypervirulent and antibiotic resistant strains stably colonize the gastrointestinal tract of in an inbred mouse population without antibiotic treatment. The small intestine is the primary site of colonization and is followed by a transition to the colon over time, without dissemination to other tissues. Our model recapitulates the disease dynamics of the metastatic K. pneumoniae strains that are able to disseminate from the gastrointestinal tract to other sterile sites. Colonization is associated with mild to moderate histopathology, no significant inflammation, and no effect on the richness of the microbiome. Our model sums up the clinical scenario in which antibiotic treatment disturbs the colonization of K. pneumoniae and results in dissemination to other tissues. Finally, we establish that the capsule polysaccharide is necessary for the colonization of the large intestine, whereas the type VI secretion system contributes to colonization across the gastrointestinal tract. IMPORTANCE Klebsiella pneumoniae is one of the pathogens that is sweeping the world in the antibiotic resistance pandemic. Klebsiella colonizes the nasopharynx and the gut of healthy subjects in an asymptomatic manner, making gut colonization a requisite for infection. This makes it essential to understand the gastrointestinal carriage in preventing Klebsiella infections. Current research models rely on the perturbation of the gut microbiome by antibiotics, resulting in an invasive infection. Here, we report a new model of K. pneumoniae gut colonization that recapitulates key features of the asymptomatic human gastrointestinal tract colonization. In our model, there is no need to disturb the microbiota to achieve stable colonization, and there is no dissemination to other tissues. Our model sums up the clinical scenario in which antibiotic treatment triggers invasive infection. We envision that our model will be an excellent platform upon which to investigate factors enhancing colonization and invasive infections and to test therapeutics to eliminate Klebsiella asymptomatic colonization.

Electromagnetic Fields Literature Analysis for Precision Medicine.

During the last century technological advances have increased the number of anthropogenic electromagnetic fields (EMFs) and therefore human exposures. In this work we have mined from more than 30,000 EMF-related publications the genes, diseases and molecular mechanisms associated with the exposure to six different subsets of EMFs. Results show 3653 unique disease MeSH terms and 9966 unique genes identified of which only 4340 genes are human. Overall, our approach highlights the molecular aspects of the increasing exposure to EMFs.

Mapping Exposome Derived Phenotypes into SNOMED Codes.

Human phenotypes define the healthy or diseased status of an individual and they arise from the complex interactions between environmental and genetic factors. The whole set of human exposures constitute the human exposome. These exposures have multiple sources including physical and socioeconomic factors. In this manuscript we have used text mining techniques to retrieve 1295 and 1903 Human Phenotype Ontology terms associated with these exposome factors and we have subsequently mapped 83% and 90% of the HPO terms respectively) into SNOMED as a clinically actionable code. We have developed a proof-of-concept approach to facilitate the integration of exposomic and clinical data.

Distribution and diversity of type VI secretion system clusters in Enterobacter bugandensis and Enterobacter cloacae.

Gram-negative bacteria use type VI secretion systems (T6SSs) to antagonize neighbouring cells. Although primarily involved in bacterial competition, the T6SS is also implicated in pathogenesis, biofilm formation and ion scavenging. Enterobacter species belong to the ESKAPE pathogens, and while their antibiotic resistance has been well studied, less is known about their pathogenesis. Here, we investigated the distribution and diversity of T6SS components in isolates of two clinically relevant Enterobacter species, E. cloacae and E. bugandensis. T6SS clusters are grouped into four types (T6SSi-T6SSiv), of which type i can be further divided into six subtypes (i1, i2, i3, i4a, i4b, i5). Analysis of a curated dataset of 31 strains demonstrated that most of them encode T6SS clusters belonging to the T6SSi type. All T6SS-positive strains possessed a conserved i3 cluster, and many harboured one or two additional i2 clusters. These clusters were less conserved, and some strains displayed evidence of deletion. We focused on a pathogenic E. bugandensis clinical isolate for comprehensive in silico effector prediction, with comparative analyses across the 31 isolates. Several new effector candidates were identified, including an evolved VgrG with a metallopeptidase domain and a Tse6-like protein. Additional effectors included an anti-eukaryotic catalase (KatN), M23 peptidase, PAAR and VgrG proteins. Our findings highlight the diversity of Enterobacter T6SSs and reveal new putative effectors that may be important for the interaction of these species with neighbouring cells and their environment.

Transcriptomics reveals shared immunosuppressive landscapes in ventilator-associated lower respiratory tract infections (VA-LRTI) patients.

BACKGROUND: Ventilator-associated pneumonia (VAP) represents a transitory status of immunoparalysis, and we hypothesized that ventilator-associated tracheobronchitis (VAT) could share also some degree of immune response to a respiratory infection. RESEARCH DESIGN AND METHODS: A prospective observational study in five medical ICUs to evaluate immunological alterations of patients with VA-LRTI. Immunological gene expression profiles in the blood using whole transcriptome microarrays in the first 24 hours following diagnosis. The area under the receiver operating characteristic curve (AUROC) was used to assess the accuracy of mRNA levels to differentiate VA-LRTI and lack of infection. A principal component analysis (PCA) was employed for analyzing the impact of each genetic expression footprint variable in explaining the variance of the cohort. RESULTS: There was overlapping between the three classes of patients encompassing gene expression levels of 8 genes (i.e. HLA, IL2RA, CD40LG, ICOS, CCR7, CD1C, CD3E). HLA-DRA was equally low among VAT and VAP patients characterizing immune depression, and significantly lower than the control group. CONCLUSIONS: Our findings suggest that VAP and VAT are not so different regarding gene expression levels suggesting a degree of immunosuppression. Our results indicate a state of immunoparalysis in respiratory infections in critically ill patients.

Defining and Scoping Participatory Health Informatics: An eDelphi Study.

BACKGROUND: Health care has evolved to support the involvement of individuals in decision making by, for example, using mobile apps and wearables that may help empower people to actively participate in their treatment and health monitoring. While the term "participatory health informatics" (PHI) has emerged in literature to describe these activities, along with the use of social media for health purposes, the scope of the research field of PHI is not yet well defined. OBJECTIVE: This article proposes a preliminary definition of PHI and defines the scope of the field. METHODS: We used an adapted Delphi study design to gain consensus from participants on a definition developed from a previous review of literature. From the literature we derived a set of attributes describing PHI as comprising 18 characteristics, 14 aims, and 4 relations. We invited researchers, health professionals, and health informaticians to score these characteristics and aims of PHI and their relations to other fields over three survey rounds. In the first round participants were able to offer additional attributes for voting. RESULTS: The first round had 44 participants, with 28 participants participating in all three rounds. These 28 participants were gender-balanced and comprised participants from industry, academia, and health sectors from all continents. Consensus was reached on 16 characteristics, 9 aims, and 6 related fields. DISCUSSION: The consensus reached on attributes of PHI describe PHI as a multidisciplinary field that uses information technology and delivers tools with a focus on individual-centered care. It studies various effects of the use of such tools and technology. Its aims address the individuals in the role of patients, but also the health of a society as a whole. There are relationships to the fields of health informatics, digital health, medical informatics, and consumer health informatics. CONCLUSION: We have proposed a preliminary definition, aims, and relationships of PHI based on literature and expert consensus. These can begin to be used to support development of research priorities and outcomes measurements.

Temporal profiling of the coding and noncoding murine cytomegalovirus transcriptomes.

The global transcriptional program of murine cytomegalovirus (MCMV), involving coding, noncoding, and antisense transcription, remains unknown. Here we report an oligonucleotide custom microarray platform capable of measuring both coding and noncoding transcription on a genome-wide scale. By profiling MCMV wild-type and immediate-early mutant strains in fibroblasts, we found rapid activation of the transcriptome by 6.5 h postinfection, with absolute dependency on ie3, but not ie1 or ie2, for genomic programming of viral gene expression. Evidence is also presented to show, for the first time, genome-wide noncoding and bidirectional transcription at late stages of MCMV infection.

Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior.

BACKGROUND: Colon cancer patients with the same stage show diverse clinical behavior due to tumor heterogeneity. We aimed to discover distinct classes of tumors based on microarray expression patterns, to analyze whether the molecular classification correlated with the histopathological stages or other clinical parameters and to study differences in the survival. METHODS: Hierarchical clustering was performed for class discovery in 88 colon tumors (stages I to IV). Pathways analysis and correlations between clinical parameters and our classification were analyzed. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the main subtype was generated using the 3-Nearest-Neighbor method. Coincidences with other prognostic predictors were assesed. RESULTS: Hierarchical clustering identified four robust tumor subtypes with biologically and clinically distinct behavior. Stromal components (p < 0.001), nuclear ß-catenin (p = 0.021), mucinous histology (p = 0.001), microsatellite-instability (p = 0.039) and BRAF mutations (p < 0.001) were associated to this classification but it was independent of Dukes stages (p = 0.646). Molecular subtypes were established from stage I. High-stroma-subtype showed increased levels of genes and altered pathways distinctive of tumour-associated-stroma and components of the extracellular matrix in contrast to Low-stroma-subtype. Mucinous-subtype was reflected by the increased expression of trefoil factors and mucins as well as by a higher proportion of MSI and BRAF mutations. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the Low-stroma-subtype distinguished low risk patients from high risk patients in the external cohort (Dukes B and C:HR = 8.56(2.53-29.01); Dukes B,C and D:HR = 1.87(1.07-3.25)). Eight different reported survival gene signatures segregated our tumors into two groups the Low-stroma-subtype and the other tumor subtypes. CONCLUSIONS: We have identified novel molecular subtypes in colon cancer with distinct biological and clinical behavior that are established from the initiation of the tumor. Tumor microenvironment is important for the classification and for the malignant power of the tumor. Differential gene sets and biological pathways characterize each tumor subtype reflecting underlying mechanisms of carcinogenesis that may be used for the selection of targeted therapeutic procedures. This classification may contribute to an improvement in the management of the patients with CRC and to a more comprehensive prognosis.

Integration of Annotated Phenotype, Gene and Chemical Text Data to Advance Exposome Informatics.

The field of phenomics has a range of biomedical informatics tools such as the Human Phenotype Ontology, providing a structured vocabulary with relationships between abnormal phenotype terms. Artificial intelligence has been widely used for entity extraction and tagging large corpora of text from PubMed and is reflected in applications such as PheneBank and PubTator. Phexpo is a tool for predicting chemical - phenotype relationships and vice-versa, although lacks the ability to decipher known relationships from unknown. Integration of these three resources can provide new meaningful relationships between phenotypes, genes and chemicals and has yet to be fully leveraged. Here we present a methodology to construct two new datasets for phenotype - gene and phenotype - chemical relationships and showcase how these datasets can be used to enhance exposome informatics.

A Comparative Analysis of Phenotypes Derived from Genes or Biomedical Literature in COVID-19.

Since the emergence of SARS-CoV-2 in November 2019, there has been an exponential production of literature due to worldwide efforts to understand the interactions between the virus and the human body. Using an "in-house" developed script we retrieved gene annotations and identified phenotype enrichments. Human Phenotype Ontology terms were retrieved from the literature using the Onassis R package. This produced both disease-gene and disease-phenotype data as well as data for gene-phenotype interactions. Overall, we retrieved 181 human phenotypes that were identified by both approaches. Further in-depth analysis of these relationships could provide further insights in the molecular mechanisms related with the observed phenotypes, answers and hypotheses for key concepts within COVID-19 research.