Syndromic approaches to persistent digestive disorders (≥14 days) in resource-constrained settings : aetiology, clinical assessment and differential diagnostics

Background: Gastrointestinal infections are among the leading causes of morbidity worldwide. In contrast to acute diarrhoea, long-lasting digestive disorders can be defined as persistent diarrhoea (≥14 days) and/or persistent abdominal pain (≥14 days). This clinical syndrome is frequently caused by intestinal infections, but its medical importance in the tropics, the range of causative pathogens and the contribution of neglected tropical diseases remain to be elucidated. Currently employed diagnostic tools for the detection of intestinal pathogens frequently lack sensitivity, and there are only few evidence-based recommendations to guide the clinical management of persistent digestive disorders in resource-constrained settings. Rapid diagnostic tests (RDTs) have become available for the diagnosis of various intestinal pathogens and hold promise to be used even in peripheral healthcare centres with only very limited laboratory infrastructure. More recently, multiplex polymerase chain reaction (PCR) assays targeting gastrointestinal pathogens have been developed, but these tests have yet to be systematically evaluated in the tropics. The current Ph.D. thesis was carried out as part of the NIDIAG project, an international research consortium that aims at developing evidence-based diagnosis-treatment algorithms for persistent digestive disorders and other common clinical syndromes in resource-constrained settings of Africa and Asia. Methods: A systematic review was performed to elucidate the aetiological spectrum of persistent digestive disorders. A study protocol, accompanied by a set of more than 30 standard operating procedures (SOPs), was developed to conduct a multi-country, prospective case-control study to investigate persistent diarrhoea (≥14 days; all individuals aged above 1 year) and persistent abdominal pain (≥14 days; all children and adolescents aged 1-18 years) in Côte d’Ivoire, Indonesia, Mali and Nepal. In the framework of a specific site assessment, a case-control study was performed in Dabou, south Côte d’Ivoire to determine the aetiology and clinical features of persistent diarrhoea. Stool samples were subjected to a host of microscopic techniques, RDTs for Clostridium difficile, Cryptosporidium spp. and Giardia intestinalis, as well as the Luminex® Gastrointestinal Pathogen Panel, a stool-based multiplex PCR. A subsequent study was conducted to assess the diagnostic accuracy of real-time PCR for detection of Strongyloides stercoralis and to compare it to a combination of microscopic methods (Baermann funnel concentration and Koga agar plate). For the first time, a previously validated, urine-based RDT for the diagnosis of Schistosoma mansoni was employed for individual management of patients presenting with digestive disorders to a hospital in Europe. Results: The systematic review identified more than 40 bacterial, parasitic (helminths and intestinal protozoa) and viral pathogens that may potentially cause persistent diarrhoea and persistent abdominal pain. In a subsequent case-control study in southern Côte d’Ivoire, 20 different intestinal pathogens were detected and >50% of all participants had co-infections. Enterotoxigenic Escherichia coli (32%) and Shigella spp. (20%) were the most prevalent bacterial pathogens, while G. intestinalis (29%) and S. stercoralis (10%) were the predominant intestinal protozoon and helminth species, respectively. With regard to infection status, there were few differences between cases and controls. Most patients with persistent diarrhoea lived in rural areas, but clinical signs and symptoms could not distinguish between specific infections. The protocol for the multi-country NIDIAG study on persistent digestive disorders adopted a case-control approach and regular follow-up visits of symptomatic patients to monitor the clinical response to treatment. A diagnostic study in south-central Côte d’Ivoire found that the application of a stool-based real-time PCR for S. stercoralis substantially improved the detection rate of this pathogen, leading to a total prevalence of 21.9%, compared to a prevalence of 10.9% according to stool microscopy. C. difficile could also be detected in stool samples from Côte d’Ivoire (5.4% prevalence according to RDT). Non-toxigenic C. difficile strains predominated and their molecular characteristics differed considerably from those observed in other settings. Prolonged storage without properly maintained cold chain only minimally affected the subsequent recovery of C. difficile and its toxins in stool culture. A point-of-care (POC) test detecting a circulating cathodic antigen (CCA) in urine was successfully utilised to confirm intestinal S. mansoni infection in migrants from Eritrea who presented to a European hospital because of persistent abdominal pain. Conclusions: Persistent digestive disorders are of considerable public health importance in Côte d’Ivoire and elsewhere, with the majority of cases being detected in rural areas. Many different causative agents may give rise to this syndrome and they can be accurately detected by the application of highly sensitive diagnostic techniques. The diversity of the potentially implicated pathogens underscores the need for a syndromic approach to persistent digestive disorders. RDTs are helpful tools for the detection of specific pathogens and may be implemented as part of diagnostic algorithms in endemic areas and in hospitals providing care for migrants and returning travellers. There is an urgent need to develop a stool-based RDT for S. stercoralis. The high asymptomatic carriage rates of intestinal pathogens call for the inclusion of healthy controls in epidemiological studies to define the specific contribution of each pathogen to the syndrome of persistent digestive disorders. Future studies employing metagenomic approaches will provide further insights into the intestinal microbiome of symptomatic patients and healthy controls

Investigation of maldi-tof mass spectrometry for assessing the molecular diversity of campylobacter jejuni and comparison with mlst and cgmlst: A luxembourg one-health study

There is a need for active molecular surveillance of human and veterinary Campylobacter infections. However, sequencing of all isolates is associated with high costs and a considerable workload. Thus, there is a need for a straightforward complementary tool to prioritize isolates to sequence. In this study, we proposed to investigate the ability of MALDI-TOF MS to pre-screen C. jejuni genetic diversity in comparison to MLST and cgMLST. A panel of 126 isolates, with 10 clonal complexes (CC), 21 sequence types (ST) and 42 different complex types (CT) determined by the SeqSphere+ cgMLST, were analysed by a MALDI Biotyper, resulting into one average spectra per isolate. Concordance and discriminating ability were evaluated based on protein profiles and different cut-offs. A random forest algorithm was trained to predict STs. With a 94% similarity cut-off, an AWC of 1.000, 0.933 and 0.851 was obtained for MLSTCC, MLSTST and cgMLST profile, respectively. The random forest classifier showed a sensitivity and specificity up to 97.5% to predict four different STs. Protein profiles allowed to predict C. jejuni CCs, STs and CTs at 100%, 93% and 85%, respectively. Machine learning and MALDI-TOF MS could be a fast and inexpensive complementary tool to give an early signal of recurrent C. jejuni on a routine basis.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Combination of MALDI-TOF Mass Spectrometry and Machine Learning for Rapid Antimicrobial Resistance Screening: The Case of Campylobacter spp.

While MALDI-TOF mass spectrometry (MS) is widely considered as the reference method for the rapid and inexpensive identification of microorganisms in routine laboratories, less attention has been addressed to its ability for detection of antimicrobial resistance (AMR). Recently, some studies assessed its potential application together with machine learning for the detection of AMR in clinical pathogens. The scope of this study was to investigate MALDI-TOF MS protein mass spectra combined with a prediction approach as an AMR screening tool for relevant foodborne pathogens, such as Campylobacter coli and Campylobacter jejuni. A One-Health panel of 224 C. jejuni and 116 C. coli strains was phenotypically tested for seven antimicrobial resistances, i.e. ciprofloxacin, erythromycin, tetracycline, gentamycin, kanamycin, streptomycin, and ampicillin, independently, and were submitted, after an on- and off-plate protein extraction, to MALDI Biotyper analysis, which yielded one average spectra per isolate and type of extraction. Overall, high performance was observed for classifiers detecting susceptible as well as ciprofloxacin- and tetracycline-resistant isolates. A maximum sensitivity and a precision of 92.3 and 81.2%, respectively, were reached. No significant prediction performance differences were observed between on- and off-plate types of protein extractions. Finally, three putative AMR biomarkers for fluoroquinolones, tetracyclines, and aminoglycosides were identified during the current study. Combination of MALDI-TOF MS and machine learning could be an efficient and inexpensive tool to swiftly screen certain AMR in foodborne pathogens, which may enable a rapid initiation of a precise, targeted antibiotic treatment.info:eu-repo/semantics/publishe

SARS-CoV-2 specific cellular and humoral immunity after bivalent BA.4/5 COVID-19 vaccination in previously infected and non-infected individuals

Knowledge is limited as to how prior SARS-CoV-2 infection influences cellular and humoral immunity after booster-vaccination with bivalent BA.4/5-adapted mRNA-vaccines, and whether vaccine-induced immunity correlates with subsequent infection. In this observational study, individuals with prior infection (n=64) showed higher vaccine-induced anti-spike IgG antibodies and neutralizing titers, but the relative increase was significantly higher in non-infected individuals (n=63). In general, both groups showed higher neutralizing activity towards the parental strain than towards Omicron subvariants BA.1, BA.2 and BA.5. In contrast, CD4 or CD8 T-cell levels towards spike from the parental strain and the Omicron subvariants, and cytokine expression profiles were similar irrespective of prior infection. Breakthrough infections occurred more frequently among previously non-infected individuals, who had significantly lower vaccine-induced spike-specific neutralizing activity and CD4 T-cell levels. Thus, the magnitude of vaccine-induced neutralizing activity and specific CD4 T-cells after bivalent vaccination may serve as a correlate for protection in previously non-infected individuals

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

Background!#!The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system.!##!Methods!#!In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings.!##!Results!#!Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host.!##!Conclusions!#!Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity