Next Article in Journal
Cortisol Levels in Infants with Central Coordination Disorders during Vojta Therapy
Previous Article in Journal
Hypomineralized Primary Teeth in Preterm Low Birth Weight Children and Its Association with Molar Incisor Hypomineralization—A 3-Year-Prospective Study
Previous Article in Special Issue
Novel Biomarkers Differentiating Viral from Bacterial Infection in Febrile Children: Future Perspectives for Management in Clinical Praxis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Children
Volume 8
Issue 12
10.3390/children8121112
children-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Acute Infectious Gastroenteritis: The Causative Agents, Omics-Based Detection of Antigens and Novel Biomarkers

by
Haziqah Hasan
1,
Nor Ashika Nasirudeen
1,
Muhammad Alif Farhan Ruzlan
1,
Muhammad Aiman Mohd Jamil
1,
Noor Akmal Shareela Ismail
2,
Asrul Abdul Wahab
3 and
Adli Ali
1,*
1
Department of Pediatric, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Kuala Lumpur 56000, Malaysia
2
Department of Biochemistry, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Kuala Lumpur 56000, Malaysia
3
Department of Medical Microbiology and Immunology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Kuala Lumpur 56000, Malaysia
*
Author to whom correspondence should be addressed.
Children 2021, 8(12), 1112; https://doi.org/10.3390/children8121112
Submission received: 1 October 2021 / Revised: 19 November 2021 / Accepted: 22 November 2021 / Published: 2 December 2021
(This article belongs to the Special Issue Advances in Pediatric Infection and Immunity)
Browse Figure
Versions Notes

Abstract

:
Acute infectious gastroenteritis (AGE) is among the leading causes of mortality in children less than 5 years of age worldwide. There are many causative agents that lead to this infection, with rotavirus being the commonest pathogen in the past decade. However, this trend is now being progressively replaced by another agent, which is the norovirus. Apart from the viruses, bacteria such as Salmonella and Escherichia coli and parasites such as Entamoeba histolytica also contribute to AGE. These agents can be recognised by their respective biological markers, which are mainly the specific antigens or genes to determine the causative pathogen. In conjunction to that, omics technologies are currently providing crucial insights into the diagnosis of acute infectious gastroenteritis at the molecular level. Recent advancement in omics technologies could be an important tool to further elucidate the potential causative agents for AGE. This review will explore the current available biomarkers and antigens available for the diagnosis and management of the different causative agents of AGE. Despite the high-priced multi-omics approaches, the idea for utilization of these technologies is to allow more robust discovery of novel antigens and biomarkers related to management AGE, which eventually can be developed using easier and cheaper detection methods for future clinical setting. Thus, prediction of prognosis, virulence and drug susceptibility for active infections can be obtained. Case management, risk prediction for hospital-acquired infections, outbreak detection, and antimicrobial accountability are aimed for further improvement by integrating these capabilities into a new clinical workflow.

Graphical Abstract

1. Introduction

AGE is defined as a diarrhoeal disease of rapid onset presenting with the incidence of three or more soft or liquid stools, or three bouts of vomiting per 24 h, with addition of abdominal pain, or fever [1,2]. This is due to the damage at the villous brush border of the intestine, which reduces the capacity to absorb intestinal contents and subsequently results in osmotic diarrhoea. Some of the causative agents would also release their toxins which bind to the specific enterocyte receptors, releasing chloride ions into the intestinal lumen which eventually causes secretory diarrhoea [3,4].
Acute infectious gastroenteritis (AGE) often affects children aged below 5 years old and causes the second highest mortality rate globally after pneumonia [5,6]. The condition is more common in developing countries than in developed countries. There have been estimated to be about 125 million gastroenteritis cases among infants 0–11 months of age and 450 million cases in children 1–4 years of age, prominently in developing countries [7]. AGE undeniably contributes to social and emotional impacts either to the parents or children, together with financial burdens. Extra expenditure is required to purchase diapers, doctor’s consultation, and medications, which some found financially bothersome [8]. Additionally, children will have to endure embarrassment and fright, whereas parents might suffer from fatigue and irritability during that period [9].
Considering that each causative pathogen of AGE has a different course of diseases and complications, different management and prevention strategies are required. Thus, identifying the correct causative pathogen, especially differentiating if it is either bacterial or viral in origin, and also predicting which patient likely requires more extensive treatment, will help with the management plan and reduction in comorbidities. Thus, this review will explore the current available biomarkers and antigens available for the diagnosis and management of the different causative agents of AGE, and subsequently, intends to look at the application of omics technologies in elucidating and discovering various infectious agents and novel biomarkers related in the management of AGE.

2. Causative Agents of AGE

Viruses, bacteria, and parasites are among the most common infectious agents causing AGE in children. Amongst them, viruses such as Rotavirus and Norovirus contribute to the greatest rate of infection. In addition to that, astrovirus, adenovirus, and bacteria (Salmonella and Eschrichia coli) as well as parasites (Entamoeba histolytica) are also equally prominent. These agents are transmitted to the host via various routes such as faeco–oral, person-to-person, and by fomites. Table 1 represents the causative agents from the highest prevalent to the less common (virus > bacteria > parasite) and their current methods of detection.

2.1. Rotavirus

Rotavirus is the most common agent causing AGE in children worldwide [10,11,12,13,14,15]. It has been suggested to be one of the most pathogenic causative agents in AGE which correlates with infectious diarrhoea, vomiting, and higher frequency of fever [13,16,17,18]. It was mostly reported among children aged 0–14 years old, with the highest incidence among children less than 5 years [14,15,16,19,20,21]. The prevalence was highly reported during the dry season [15,21], bottle-fed children [15,22,23], and children with group A blood type [15,24,25]. Moreover, laboratory investigations revealed a significantly high level of serum transaminase among children infected with rotavirus [26,27,28]. Among many studies conducted worldwide, it was found that rotavirus infected children have a high chance of developing dehydration as a complication, and thus, must be closely monitored [7,16,29,30].

2.2. Norovirus

Norovirus is an emerging cause of acute gastroenteritis, responsible for approximately 17–18% of all acute gastroenteritis cases worldwide, especially among developed countries [31,32,33,34,35]. The age group under 1 year old has the highest frequency of norovirus infection with additional risk factors which include male sex [34]. Norovirus is detected throughout the year, with the autumn and winter seasons observed to report a higher frequency of cases [31,36,37]; the detection rate of norovirus cases correlates positively with humidity [37]. Co-infection with rotavirus [38,39], astrovirus [40], and Salmonella [39] may occur in certain cases. Norovirus infections are observed to cause more severe symptoms of gastroenteritis in children compared with rotavirus, especially after the introduction of the rotavirus vaccination period [41]. Individuals with AB blood group have less susceptibility towards GII.4 noroviruses, whereas those with the O blood group are more susceptible to GI.4, GII.4, GII.17, and GII.18-Nica viruses [42]. GII.4 is the most common norovirus genotype causing infection in children [34,43,44]. However, recent epidemiological data observed that GII.2[P16] is currently an emerging norovirus strain in East Asia and Europe [45]. Norovirus-infected patients are more likely to have a longer duration of infection and more frequent vomiting in a day, but less likely to report fever in comparison with other causes of infective gastroenteritis [46].

2.3. Astrovirus

With an astrovirus-causing acute gastroenteritis’ global average incidence of 11%, the highest prevalence of human astrovirus (HAstV) infections was in the group of children between 37 and 48 months old [47,48]. HAstV infection mainly occurs during the dry season in the African continent; meanwhile, the highest occurrence reported in the tropical areas is often in the rainy season and winter season in temperate climate countries [47,49]. Patients usually manifested with diarrhoea, fever, vomiting, and abdominal pain [48,50].

2.4. Enteric Adenovirus Serotypes 40 and 41

Between 2.3 and 5% of the diarrhoea cases in children were caused by adenoviruses (AdV) serotypes 40 and 41 [51]. Enteric adenovirus serotypes 40 and 41 account for both sporadic or epidemic gastroenteritis in infants and young children, which are detected throughout the year with a summer peak between May and July [51,52,53]. Those infected with this pathogen will acquire mild fever and vomiting, abdominal pain, bloody diarrhoea, respiratory symptoms such as cough, and/or secondary lactose malabsorption [53,54]. Patients with adenovirus gastroenteritis have a significantly higher CRP (mean 3.4 mg/dL) and ESR value (mean 24 mm/h) compared with other gastroenteritis pathogens, and pulmonary-associated symptoms and vomiting frequency are increased in patients with this infective gastroenteritis [55]. Intravenous cytosine nucleotide analogue (CDV) that inhibits DNA polymerase has the highest in vitro activity against adenovirus, and is the preferred therapeutic agent. Elevation in lymphocyte counts (specifically CD4) were correlated with the clearance of AdV infection and improvement in survival [56,57].

2.5. Salmonella

Salmonella has become a major foodborne pathogen across the globe, causing about 3.4 million cases and 681,316 annual deaths, with 63.7% of cases occurring in children under 5 years of age [58,59,60]. There were at least 150 non-typhoidal Salmonella serotypes that can cause gastroenteritis, with Salmonella Typhimurium and Salmonella Enteritidis being the most common serotypes [59,61,62]. A study in Greece recorded that the highest rate of infection was in August, with infants being the most vulnerable group [63]. The contributing factor of salmonellosis was mainly related to consumption of contaminated food and poor clean water supply [64,65]. Salmonellosis can cause the increase in C-reactive protein values (CRP), erythrocyte sedimentation rate (ESR) and body temperature [66]. In terms of management, the recommended empiric parenteral therapy includes cefotaxime or ceftriaxone, whereas oral therapy includes amoxicillin, trimethoprim-sulfamethoxazole, or azithromycin. Salmonella isolates have a high resistance towards at least one antimicrobial agent [61,67], especially towards clindamycin, oxacillin, penicillin, and vancomycin, thus antibiotic susceptibilities of Salmonella must be determined for the targeted antibiotic therapy [62].

2.6. Escherichia coli

The WHO Global Burden of Foodborne Diseases report estimates that more than 300 million illnesses and nearly 200,000 deaths are caused by diarrheagenic Escherichia coli (DEC) globally each year. DEC is one of the major causal agents of diarrhoea in children under 5 years of age in developing countries [68,69,70], whereas children under 2 years of age are at the highest risk of infection with Enteropathogenic Escherichia coli [71,72] and Escherichia coli O157:H7 [71,73]. However, the major cause of paediatric infections in certain areas such as Ahvaz, Iran, were non-O157:H7 E. coli [74]. The incidence of non-O157 Shiga Toxin-producing Escherichia coli has been increasing in recent years, including those caused by serotypes O26, O45, O103, O111, O121, and O145 [75]. Co-infections can occur especially between EPEC and Campylobacter spp. [76]. Interestingly, Enteropathogenic Escherichia coli cases are less frequently detected in Malaysia and its similar geographical/climatic areas, in comparison with a country such as Iran where it has been reported that acute gastroenteritis was greatly caused by this strain [77]. Most DEC are sensitive to ciprofloxacin and the empirical antibiotic of choice [78,79].

2.7. Entamoeba histolytica

Other than viruses and bacteria, parasites such as Entamoeba histolytica also play a role in causing acute gastroenteritis in children [80,81,82]. Children infected with Entamoeba histolytica were mostly presented with tenesmus [81,82,83], fever [81,82], vomiting [81,84], abdominal cramps [81,83,84], and bloody diarrhoea [8,82,83]. Through laboratory investigations, it was found that infection with Entamoeba histolytica results in leukocytosis [80,81,84,85], elevation of CRP [74,78,79,80,84,85], elevation of ESR [81], elevation of serum alkaline phosphatase, and serum transaminase levels [81,86]. Eating unwashed or raw vegetables [86,87,88,89] and poor water hygiene [82,90,91] were identified to increase the risk of Entamoeba histolytica infection.

3. Biomarkers in the Detection of Common Aetiological Agents of AGE

There are various biomarkers utilised in the detection of aetiological agents of AGE via various platforms, with the most common being the detection of antigens via enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA), and immunochromatography. Moreover, detection of genes could also be conducted via procedures such as real-time PCR (RT-PCR) and multiplex real-time PCR. These are cost-effective methods that can be implemented in the future for detection of biomarkers identified via omics technologies. The breadth of the available tests, their sensitivity, and specificity are summarized in Table 1.

3.1. Rotavirus

As the most common inflicted pathogen causing AGE in children, several biomarkers have been developed and available commercially for the detection of rotavirus. The widely available biomarker platform utilized is the enzyme immunoassay (EIA) to screen for the rotavirus antigen [10,11,13,15,19,22,26,92,93,94]. Amongst EIA kit used were Premier Rotaclone, Meridian Bioscience Inc., Cincinnati, OH, USA [10,11,12,19,93,94], RIDASCREEN Rotavirus R Biopharm AG, Darmstadt, Germany [15,93], and ProSpect Rotavirus Test, Oxoid Ltd., UK [22,93]. Rotavirus antigens can also be detected by using enzyme-linked immunosorbent assay (ELISA) [12,16,18,20,28,30] which includes ELISA kits such as Premier Rotaclone, Meridian Bioscience, Inc. [12], Fecal Rotavirus Antigen ELISA Kit (EDI, CA, USA) [16], ProSpecTM Rotavirus Microplate Assay, Oxoid [20] and Rota Antigen Test Device, Cambridge [28]. ELISA can also be used in the detection of rotavirus-specific IgM [29]. Other methods in detection of rotavirus antigen were immunochromatography [25,27] and latex agglutination [23,92,95]. In addition, polyacrylamide gel electrophoresis (PAGE) was carried out to determine the electropherotype of rotavirus strains [10,19,92]. Moreover, samples that were rotavirus positive for ELISA or EIA were sent for genotyping using reverse-transcription polymerase chain reaction (RT-PCR) to determine whether they belong to particular G/P genotypes [11,16,19,20,25,29,96,97]. A multiplex real-time RT-PCR is an advanced approach for a high-throughput rotavirus genotype characterization for monitoring circulating rotavirus wild-type strains, which is more robust in identifying a novel strain [98].

3.2. Norovirus

Viral RNA and antigens are the main biomarkers for detection of norovirus infection. Real-time quantitative polymerase chain reaction, Multiplex Gastrointestinal Platforms, enzyme immunoassays (EIAs) and genotyping are the main methods used in laboratory diagnosis of norovirus [99]. Cepheid Xpert® Norovirus kit automates sample processing, nucleic acid extraction, and real-time reverse transcription polymerase chain reactions (RT-PCRs) for detection and differentiation of norovirus GI and GII, which account for the majority of norovirus infections worldwide [100,101]. Another real-time PCR platform, RIDA®GENE Norovirus, can also be used as an alternative in detecting the virus [102]. Although PCRs are highly sensitive and specific, they are expensive and require specialized techniques and equipment. Rapid diagnostic tests are usually carried out during outbreak screening and patient management, which include immunochromatographic test, enzyme immunoassay (EIA), enzyme-linked immunosorbent assay (ELISA) and fluorescence immunoassay (FIA). RIDA®QUICK Norovirus (R-Biopharm AG, Darmstadt, Germany) is one of the most used rapid immunochromatographic tests to detect norovirus [103,104,105]. Other immunochromatographic tests that are still used include QuickNaviTM—Norovirus 2 [106,107]. RIDASCREEN® Norovirus 3rd Generation is an example of ELISA that is still currently in use [108,109]. For FIA, the Automated Fluorescent Immunoassay System NORO (AFIAS-Noro) assays (Boditech Med Inc, Gangwon-do, South Korea) are newly developed diagnostic tests for norovirus infections [95].

3.3. Astrovirus

Stool samples can be investigated using RT-PCR to detect the presence of human astrovirus (HAstV) [47,48,55]. One of the available kits is the RT-PCR Luminex Assay, with which a portion of the ORF2 capsid region is targeted by using a set of specific reverse primers labeled with biotinTEG at 5′-ends and specific probes sequences [110]. A one-step, accelerated, real-time RT-LAMP (rRTLAMP) assay can also be used by targeting the 5′-end of the capsid gene for rapid and quantitative detection of HAstV [111,112].

3.4. Enteric Adenovirus Serotypes 40 and 41

Adenovirus antigen and hexon-coding gene in enteric adenovirus serotypes 40 and 41 can be recognised and used for screening and detection methods of this pathogenic agent infection. BioNexia RotaAdeno and RIDA Quick Rota-Adeno-Combi R-Biopharm, which are the immunochromatographic tests (ICT) and LIAISON Adenovirus chemiluminescence immunoassays (CLIA) can be utilised to detect enteric adenovirus antigen [113,114]. The samples from ICT and LIAISON CLIA can subsequently undergo RT-PCR for genotyping of hexon-coding genes by using a specific TaqMan Array Card, which is a 384-well singleplex real-time PCR format that has been recognised to detect multiple infection targets [115,116].

3.5. Salmonella

As for Salmonella infection, the virulence genes include flagellin (filcC), invA, invF, sitC, hilAgene, sipC, sipF genes as well as heat stable enterotoxin gene, parE [117]. Multiplex real-time PCR such as RIDA GENE-gastrointestinal kits, EntericBio real-time Gastro Panel I, and Seeplex Diarrhea ACE detection has allowed a more rapid detection of multiple targets in a short period of time and some of the tests was followed by hybridisation to microarray/macroarray to achieve multiparametric detection of AGE aetiological agents [118]. In terms of sensitivity and specificity, RIDA GENE-gastrointestinal kits were reported to have 25% sensitivity and 99.7% specificity [119,120,121]. As for EntericBio real-time Gastro Panel I, its sensitivity and specificity were much higher, which were 100% and 97.8%, respectively [120]. Seeplex Diarrhea ACE has a sensitivity of 40–100% and specificity of 96–100% [119,122,123].

3.6. Escherichia coli

Most of the current omics approaches were focused on the detection of Shiga Toxin-producing Escherichia coli (STEC) infections. This is due to the fact that accurate diagnosis of STEC infection is very crucial because appropriate early treatment decreases the risk of serious complications and improves overall patient outcome, especially in children [124,125]. Although non-O157 serotypes account for the majority of STEC infections, they are significantly under-reported because frontline microbiology laboratories mainly focus on the detection of O157 STEC using specific agar-based methods [126]. CHROMagar STEC is a new chromogenic medium invented to improve detection of STEC, which detects O157 and non-O157 STEC through a chromogenic substrate [126,127]. However, PCR is a more sensitive test than culture [126,127]. RIDA®GENE real-time PCR kits EAEC, EHEC/EPEC, and ETEC/EIEC (R-Biopharm, Darmstadt, Germany) all can be used to detect the aatA and aggR, eae, and elt and estA genes of Enteroaggregative, Enteropathogenic, and Enterotoxigenic Escherichia coli, respectively [128]. These will ensure that different pathotypes of diarrheagenic Escherichia coli can be detected and differentiated successfully.

3.7. Entamoeba histolytica

Entamoeba histolytica infection can cause a significant decrease in serum leptin and has been suggested to be a potential biomarker for this pathogenic infection [129], which can be detected using the ELISA technique (kit supplied by RayBiotech.Inc, Guangzhou, China). Moreover, there was also a marked increase in HDL, obestatin, calprotectin and SIgA concentration level with a concurrent decrease in cholesterol, triglyceride, LDL and VLDL concentration levels. All of these serums can be analysed and measured using ELISA techniques [130]. ELISA (Techlab II Entamoeba histolytica) can also be used to detect Entamoeba histolytica antigen presented in stool with a specificity of 100% but with a low sensitivity of 19.2% [131]. Thus, multiplex PCR is a more favourable option as it has sensitivity of 100% with specificity of 95.8% [132]. During progression of amoebiasis, a small non-coding RNA known as microRNA (miRNA) is involved in promoting apoptosis in epithelial colon cells and comprehensive profiling of miRNA using Taqman Low-Density Arrays showed a significant interaction between miRNA and parasite presented [133]. Taqman Low-Density Arrays has a sensitivity of 92% and a specificity of 100% in diagnosis of Entamoeba histolytica infection [134].
Table
Table 1. Biomarkers of aetiological agents and detection methods.
Table 1. Biomarkers of aetiological agents and detection methods.
AgentBiomarkerDetection MethodBrandSensitivitySpecificityReferences
RotavirusRotavirus antigenELISARota Antigen Test Device, Cambridge86–98%92–96%[28]
EIAPremier Rotaclone, Meridian Bioscience Inc., Cincinnati, OH, USA76.8–77.8%100%[93,94]
RIDASCREEN® Rotavirus82.1–97.8%99.1–100%[93]
ProSpect Rotavirus Test, Oxoid Ltd., UK75%100%[93]
Rotavirus RNART-PCRPrimerdesign Genesig® Kit100%100%[97]
Real-time RT-PCRGeneAmp EZ rTth RNA PCR kit (Applied Biosystems, Inc., Foster City, CA, USA)98.8–100%99.7–100%[98]
NorovirusNorovirus antigen ICT RIDA®QUICK Norovirus N1402 72.8–87% 97–99.5% [117,118]
QuickNaviTM Norovirus 2 27.5% 97.7% [120]
ELISA RIDASCREEN® Norovirus 3rd Generation 84.6–85.7%>96%[121,122]
FIAAFIAS-Noro66%97.6%[95]
Norovirus RNAReal-time RT-PCRCepheid Xpert® Norovirus100%100%[114]
Real-time PCRRIDA®GENE Norovirus98%98%[102]
AstrovirusORF2 geneRT-PCRRT-PCR Luminex Assay100%100%[123]
rRTLAMP Assay94%100%[124,125]
Enteric Adenovirus Serotypes 40 and 41Adenovirus antigenICTBioNexia RotaAdeno60% 98.8% [126]
RIDA Quick Rota-Adeno-Combi R-Biopharm AG 72.7% 98.2% [127]
CLIA LIAISON Adenovirus 77% 98.8% [126]
Hexon-coding geneRT-PCR TaqMan Array Card 100% 100% [129]
SalmonellaSalmonella virulence genesMultiplex PCRRIDA®GENE-gastrointestinal kits25%99.7%[103,104,105]
EntericBio real-time Gastro Panel I100%97.8%[104]
Seeplex Diarrhea ACE40–100%96–100%[103,106,107]
Shiga Toxin-producing Escherichia coli (STEC)Shiga toxins (stx) serotypesMultiplex PCRSeeplex Diarrhea ACE100%99.6–100%[110]
Real-time PCRTaqMan™ STEC100%100%
Culture mediumCHROMagar STEC84.6–85.7%87–95.8%
Enteropathogenic Escherichia coli (EPEC)eae geneReal-time PCR RIDA®GENE EHEC/EPEC 84% 97% [112]
Enterotoxigenic Escherichia coli (ETEC)elt and estA genes RIDA®GENE ETEC/EIEC 83% 100%
Enteroaggregative Escherichia coli (EAEC)aatA and aggR genes RIDA®GENE EAEC 69% 100%
Entamoeba histolyticaEntamoeba histolytica antigenELISA Techlab II Entamoeba histolytica19.2% 100% [131,132,133]
Multiplex PCR Performed on Mx3005P detection system 100% 95.8% [134]
microRNA (miRNA)RT-PCRTaqman Low-Density Arrays92%100%[135]

4. Omics-Based Technologies for AGE Diagnosis and Management

Recent advancement in omics technologies has enabled researchers to further elucidate the potential causative agents for AGE, as only known pathogens can be detected and identified by the current molecular target-dependent techniques. Metagenomics based on next-generation sequencing (NGS) platform, is a target-independent assay that allows concurrent detection and genomic characterization of all microorganisms present in a sample [136]. The latest NGS platform was first applied in AGE studies to look at the most prevalent genotype in rotavirus. The method was conducted on rotavirus positive specimens to further elucidate the most prevalent genotype in various geographical areas [135,137,138,139,140]. Metagenomic approach using NGS can also be used to analyze norovirus strain diversity [141,142,143]. Additionally, next generation whole genome sequencing performed on fecal samples is proposed as a powerful tool for the diagnosis and genetic analysis of norovirus infection [144,145].
Similarly, astrovirus infection can be detected using the NGS platform via metagenomic analysis [136,146]. Amino acid sequence of the capsid region (ORF2) classified the identified HAstV infection into the “classical” genotypes (Mamastrovirus 1 (MAstV-1) species) or the “novel” recombinant genotypes (MAstV-6, 8, and 9 species) [147]. The other astrovirus genotypes that can be detected using NGS are also listed in Table 2 [146]. By using the similar approach, enteric adenovirus serotypes 40 and 41 can be specifically detected, in addition it is able to correctly identify and differentiate the different genotypes of human adenovirus (HAdV) A–G [136,148]. Furthermore, Entamoeba histolytica has also been analysed for its respective strains using NGS platform [149] (Table 2).
Single-cell transcriptomics is the latest omics approach to unravel the dynamics of cellular reconstruction by measuring the concentration of mRNA to thousands of genes in each cell, which can be applied in the study of gastrointestinal pathogens [150]. Transcriptomics analysis using Serial Analysis and Cap Analysis of Gene Expression (SAGE/CAGE), and microarrays also have been used to identify the present of nadA in detection of Salmonella enterica [151,152,153] and EHEC EDL933 in detection of Escherichia coli [154].
Proteomics is specially dedicated to protein analysis, by looking at the different composition of amino acids. This platform has been growing steadily and widely utilized with the supplementation of advances in both mass spectrometry and bioinformatics [155]. In detection of Salmonella Enteritidis, proteomic approaches have been used to detect isogenic Type Three Secretion System-I (TTSS-I) known as M1511 and its wild-type isolate, P125109 using a high-resolution Fourier transform mass spectrometer [156]. For Escherichia coli identification, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF MS) can also be used because it is a rapid, low cost, reliable and accurate proteomic method for E. coli identification up to the subspecies level compared with classical culture microbiological techniques [157,158].
Metabolomics belongs to the ‘omics’ family that deals with the characterization of the set of metabolites in a given biological system [159]. As such, metabolomics analysis can be used to detect Salmonella enterica serovar Typhimurium. The most widely used techniques in metabolomics analysis are gas chromatography-mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), and capillary electrophoresis coupled to mass spectrometry (CE-MS) [154,160,161]. Liquid chromatography–mass spectrometry (LC-MS) is also the metabolomic analysis technique used to detect changes in gut microbiota in children with diarrhoea caused by diarrhoeagenic Escherichia coli (DEC), as DEC-infected children and healthy children have a statistically different composition of microbiota [162].
Table
Table 2. Omics Technologies for Elucidation of AGE Causative Agents.
Table 2. Omics Technologies for Elucidation of AGE Causative Agents.
OmicsPlatformInfectious Agents DetectedPotential BiomarkersReferences
MetagenomicsNext Generation SequencingRotavirus
  • G1P[8]
[135]
  • G9P[8]
[135,138]
  • G3P[8]
[137]
  • G3P[6]
[137]
  • G8P[8]
[139,140]
Norovirus
  • GI genotypes
  • GII genotypes
[135,144,145]
  • GII.4
[137]
Astrovirus
  • MAstV-1
  • MAstV-6
  • MAstV-8
  • MAstV-9
[142]
  • StAstV
  • Bovine AstV
  • Deer AstV
  • Dromedary AstV
  • Porcine AstV
  • Murine AstV
  • Wild boar AstV
  • Rabbit AstV
  • Rat AstV
[141]
Adenovirus
  • HAdV A
  • HAdV B
  • HAdV C
  • HAdV D
  • HAdV E
  • HAdV F
  • HAdV G
[130]
E. histolytica
  • KU27
  • KU50
[144]
Transcriptomics
  • Serial Analysis and Cap Analysis of Gene expression (SAGE/CAGE)
  • Microarray
Salmonella entericanadA gene[155,156,157]
Enterohaemorrhagic Escherichia coliEHEC EDL933[146,147,148]
ProteomicsFourier transform mass spectrometerSalmonella enteritidis
  • TTSS-I (M1511)
  • P125109
[150]
Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF MS)Escherichia coliMass peaks ranged from approximately 3000 to 15,000 m/z for different strains of E.coli (EPEC, EIEC and DAEC strains).[151]
Metabolomics
  • Gas chromatography-mass spectrometry (GC-MS)
  • Liquid chromatography–mass spectrometry (LC-MS)
  • Capillary electrophoresis coupled to mass spectrometry (CE-MS)
Salmonella enterica Serovar Typhimurium22 metabolites were identified in greater abundance and these metabolites triggered oxidative stress.[148,154,155]
  • Liquid chromatography–mass spectrometry (LC-MS)
Diarrheagenic Escherichia coli (DEC)Higher levels of histamine and lower levels of ornithine in DEC samples than in the healthy group.[156]
Emerging omics technologies have evoked the elucidation of significant infectious agents of AGE. These multi-omics approaches can be used as the basis for the detection of the biomarkers which can be elucidated in the future through much cheaper methods such as PCR and ELISA in the clinical setting. Therefore, the technology in deciphering the role of causative agents of AGE should be explored and made accessible. Since multidrug resistance and healthcare-associated infections pose threats to current epidemic, this demand revolution in management strategies, hence multi-omics approaches can be one of the potential solutions in detecting potential biomarkers. Ability to manage infections can be transformed with routine access of pathogen genomic data, but only if we can amalgamate with other data for critical outcomes. Extensive clinical data related to pathogen genotypes in the long term will enable prediction of prognosis, virulence, and drug susceptibility for active infections. Integrating these capabilities into a new clinical approach in detecting biomarkers should improve case management, risk prediction, outbreak detection, and antimicrobial accountability of AGE.

5. Conclusions

Although rotavirus remains the main pathogen causing acute gastroenteritis in children, other pathogenic agents such as norovirus is evolving to emerge as one of the important AGE-causative agents and requires attention in the future studies. This is without ignoring the fact that bacteria and parasite pathogens also have a continuous and very relevant role in causing acute infectious gastroenteritis especially among children. With the emergence of other causative pathogens, different numerous mutations resulted in more pathogenic strains, as well as lack of reliable prognostic parameters, more robust diagnostic and predictive biomarkers need to be considered. Assuming the cost as the barrier, NGS and other omics-based approaches can be used as the fundamental methodologies for novel biomarker detection in clinical microbiology. With the wider and hopefully in the near future more accessible utilization of different omics-based approaches, these modalities should be readily considered and integrated for a more holistic, and comprehensive management of patients with AGE.

Author Contributions

Conceptualization, A.A. and N.A.S.I.; data curation, H.H., N.A.N., M.A.F.R. and M.A.M.J.; writing—original draft preparation, H.H., N.A.N., M.A.F.R. and M.A.M.J.; writing—review and editing, A.A., N.A.S.I. and A.A.W.; supervision, A.A. and N.A.S.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received internal funding from the Faculty of Medicine, UKM.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We are thankful to the Faculty of Medicine, Universiti Kebangsaan Malaysia for supporting this publication.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hartman, S.; Brown, E.; Loomis, E.; Russell, H.A. Gastroenteritis in Children. Am. Fam. Physician 2019, 99, 159–165. [Google Scholar] [PubMed]
  2. Sdiri-Loulizi, K.; Gharbi-Khelifi, H.; de Rougemont, A.; Hassine, M.; Chouchane, S.; Sakly, N.; Pothier, P.; Guédiche, M.N.; Aouni, M.; Ambert-Balay, K. Molecular Epidemiology of Human Astrovirus and Adenovirus Serotypes 40/41 Strains Related to Acute Diarrhea in Tunisian Children. J. Med. Virol. 2009, 81, 1895–1902. [Google Scholar] [CrossRef]
  3. Kelly, L.; Jenkins, H.; Whyte, L. Pathophysiology of Diarrhoea. Paediatr. Child Health 2018, 28, 520–526. [Google Scholar] [CrossRef]
  4. Whyte, L.A.; Jenkins, H.R. Pathophysiology of Diarrhoea. Paediatr. Child Health 2012, 22, 443–447. [Google Scholar] [CrossRef]
  5. Farthing, M.; Salam, M.A.; Lindberg, G.; Dite, P.; Khalif, I.; Salazar-Lindo, E.; Ramakrishna, B.S.; Goh, K.-L.; Thomson, A.; Khan, A.G.; et al. Acute Diarrhea in Adults and Children. J. Clin. Gastroenterol. 2013, 47, 12–20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Faure, C. Role of Antidiarrhoeal Drugs as Adjunctive Therapies for Acute Diarrhoea in Children. Int. J. Pediatrics 2013, 2013, 612403. [Google Scholar] [CrossRef] [Green Version]
  7. Parashar, U.D.; Nelson, E.A.S.; Kang, G. Diagnosis, Management, and Prevention of Rotavirus Gastroenteritis in Children. BMJ 2013, 347, f7204. [Google Scholar] [CrossRef] [Green Version]
  8. Loganathan, T.; Lee, W.S.; Lee, K.F.; Jit, M.; Ng, C.W. Household catastrophic healthcare expenditure and impoverishment due to rotavirus gastroenteritis requiring hospitalization in Malaysia. PLoS ONE 2015, 10, e0125878. [Google Scholar]
  9. Marchetti, F.; Vetter, V.; Conforti, G.; Esposito, S.; Bonanni, P. Parents’ insights after pediatric hospitalization due to rotavirus gastroenteritis in Italy. Hum. Vaccines Immunother. 2017, 13, 2155–2159. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  10. Gupta, S.; Chaudhary, S.; Bubber, P.; Ray, P. Epidemiology and Genetic Diversity of Group A Rotavirus in Acute Diarrhea Patients in Pre-Vaccination Era in Himachal Pradesh, India. Vaccine 2019, 37, 5350–5356. [Google Scholar] [CrossRef] [PubMed]
  11. Giri, S.; Nair, N.P.; Mathew, A.; Manohar, B.; Simon, A.; Singh, T.; Suresh Kumar, S.; Mathew, M.A.; Babji, S.; Arora, R.; et al. Rotavirus Gastroenteritis in Indian Children. BMC Public Health 2019, 19, 69. [Google Scholar] [CrossRef]
  12. Gopalkrishna, V.; Joshi, M.S.; Chavan, N.A.; Shinde, M.S.; Walimbe, A.M.; Sawant, P.M.; Kalrao, V.R.; Dhongade, R.K.; Bavdekar, A.R. Prevalence and Genetic Diversity of Gastroenteritis Viruses in Hospitalized Children. J. Med. Virol. 2021, 93, 4805–4816. [Google Scholar] [CrossRef] [PubMed]
  13. Stanyevic, B.; Sepich, M.; Biondi, S.; Baroncelli, G.I.; Peroni, D.; Di Cicco, M. The Evolving Epidemiology of Acute Gastroenteritis in Hospitalized Children in Italy. Eur. J. Pediatrics 2021. [Google Scholar] [CrossRef]
  14. Salim, N.A.B.M.; Naik, D.G.; Fuad, M.D.F. Prevalence of Rotavirus Diarrhea in Children of Perak, Malaysia. Indian J. Public Health Res. Dev. 2017, 8, 285. [Google Scholar] [CrossRef]
  15. Ojobor, C.D.; Olovo, C.V.; Onah, L.O.; Ike, A.C. Prevalence and Associated Factors to Rotavirus Infection in Children Less than 5 Years in Enugu State, Nigeria. VirusDisease 2020, 31, 316–322. [Google Scholar] [CrossRef] [PubMed]
  16. Dong, S.; Huang, D.; Wang, Z.; Zhang, G.; Zhang, F.; Sai, L. Clinical and Molecular Epidemiological Characterization of Rotavirus Infections in Children under Five Years Old in Shandong Province, China. Arch. Virol. 2021, 166, 2479–2486. [Google Scholar] [CrossRef]
  17. Ghoshal, V.; Nayak, M.K.; Misra, N.; Kumar, R.; Reddy, N.S.; Mohakud, N.K. Surveillance and Molecular Characterization of Rotavirus Strains Circulating in Odisha, India after Introduction of Rotavac. Indian J. Pediatrics 2021, 88, 41–46. [Google Scholar] [CrossRef]
  18. Zeng, X.-D.; Hu, W.-G. Spontaneous Remission of Infantile Spasms Following Rotavirus Gastroenteritis. Neurol. Sci. 2020, 42, 253–257. [Google Scholar] [CrossRef]
  19. Amit, L.N.; Mori, D.; John, J.L.; Chin, A.Z.; Mosiun, A.K.; Jeffree, M.S.; Ahmed, K. Emergence of Equine-like G3 Strains as the Dominant Rotavirus among Children under Five with Diarrhea in Sabah, Malaysia during 2018–2019. PLoS ONE 2021, 16, e0254784. [Google Scholar] [CrossRef]
  20. Shrestha, S.; Thakali, O.; Raya, S.; Shrestha, L.; Parajuli, K.; Sherchand, J.B. Acute Gastroenteritis Associated with Rotavirus A among Children Less than 5 Years of Age in Nepal. BMC Infect. Dis. 2019, 19, 456. [Google Scholar] [CrossRef] [Green Version]
  21. Ouedraogo, N.; Ngangas, S.M.T.; Bonkoungou, I.J.O.; Tiendrebeogo, A.B.; Traore, K.A.; Sanou, I.; Traore, A.S.; Barro, N. Temporal Distribution of Gastroenteritis Viruses in Ouagadougou, Burkina Faso: Seasonality of Rotavirus. BMC Public Health 2017, 17, 274. [Google Scholar] [CrossRef] [Green Version]
  22. Alkoshi, S.I.M.; Miftah, A.; Ernst, K.; Nagib, S. Frequency of Rotavirus Infection among Children in North-Eastern Region of Libya: A Hospital-Based Study from Almarj. Libyan J. Med. Sci. 2017, 1, 76. [Google Scholar] [CrossRef]
  23. Abbas, A. Role of rotavirus as the cause of acute pediatric diarrhea in Al-Diwaniyah, Iraq. Al-Qadisiyah J. Vet. Med. Sci. 2019, 18, 1125. [Google Scholar]
  24. Elnady, H.G.; Samie, O.M.A.; Saleh, M.T.; Sherif, L.S.; Abdalmoneam, N.; Kholoussi, N.M.; Kholoussi, S.M.; EL-Taweel, A.N. ABO Blood Grouping in Egyptian Children with Rotavirus Gastroenteritis. Gastroenterol. Rev. 2017, 3, 175–180. [Google Scholar] [CrossRef] [Green Version]
  25. Pérez-Ortín, R.; Vila-Vicent, S.; Carmona-Vicente, N.; Santiso-Bellón, C.; Rodríguez-Díaz, J.; Buesa, J. Histo-Blood Group Antigens in Children with Symptomatic Rotavirus Infection. Viruses 2019, 11, 339. [Google Scholar] [CrossRef] [Green Version]
  26. Wiegering, V.; Kaiser, J.; Tappe, D.; Weißbrich, B.; Morbach, H.; Girschick, H.J. Gastroenteritis in Childhood: A Retrospective Study of 650 Hospitalized Pediatric Patients. Int. J. Infect. Dis. 2011, 15, e401–e407. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Akelma, A.Z.; Kütükoğlu, I.; Köksal, T.; Çizmeci, M.N.; Kanburoglu, M.K.; Çatal, F.; Mete, E.; Bozkaya, D.; Namuslu, M. Serum Transaminase Elevation in Children with Rotavirus Gastroenteritis: Seven Years’ Experience. Scand. J. Infect. Dis. 2012, 45, 362–367. [Google Scholar] [CrossRef]
  28. Erdogan, S. Serum Transaminase Elevation in Patients with Rotavirus Gastroenteritis. J. Clin. Anal. Med. 2017, 8, 488–491. [Google Scholar] [CrossRef]
  29. Huyen, D.T.T.; Hong, D.T.; Trung, N.T.; Hoa, T.T.N.; Oanh, N.K.; Thang, H.V.; Thao, N.T.T.; Hung, D.M.; Iijima, M.; Fox, K.; et al. Epidemiology of Acute Diarrhea Caused by Rotavirus in Sentinel Surveillance Sites of Vietnam, 2012–2015. Vaccine 2018, 36, 7894–7900. [Google Scholar] [CrossRef]
  30. Bhatnagar, S.; Srivastva, G. Clinical Profile of Children (0–5 Years) with RotaVirus Diarrhea. Int. J. Contemp. Pediatrics 2017, 4, 947. [Google Scholar] [CrossRef] [Green Version]
  31. Haddadin, Z.; Batarseh, E.; Hamdan, L.; Stewart, L.S.; Piya, B.; Rahman, H.; Spieker, A.J.; Chappell, J.; Wikswo, M.E.; Dunn, J.R.; et al. Characteristics of GII.4 Norovirus Versus Other Genotypes in Sporadic Pediatric Infections in Davidson County, Tennessee, USA. Clin. Infect. Dis. 2021, 73, e1525–e1531. [Google Scholar] [CrossRef]
  32. Nguyen, G.T.; Phan, K.; Teng, I.; Pu, J.; Watanabe, T. A Systematic Review and Meta-Analysis of the Prevalence of Norovirus in Cases of Gastroenteritis in Developing Countries. Medicine 2017, 96, e8139. [Google Scholar] [CrossRef]
  33. Lopman, B.A.; Steele, D.; Kirkwood, C.D.; Parashar, U.D. The Vast and Varied Global Burden of Norovirus: Prospects for Prevention and Control. PLoS Med. 2016, 13, e1001999. [Google Scholar] [CrossRef]
  34. Farahmand, M.; Moghoofei, M.; Dorost, A.; Shoja, Z.; Ghorbani, S.; Kiani, S.J.; Khales, P.; Esteghamati, A.; Sayyahfar, S.; Jafarzadeh, M.; et al. Global Prevalence and Genotype Distribution of Norovirus Infection in Children with Gastroenteritis: A Meta-analysis on 6 Years of Research from 2015 to 2020. Rev. Med. Virol. 2021, e2237. [Google Scholar] [CrossRef]
  35. Ahmed, S.M.; Hall, A.J.; Robinson, A.E.; Verhoef, L.; Premkumar, P.; Parashar, U.D.; Koopmans, M.; Lopman, B.A. Global Prevalence of Norovirus in Cases of Gastroenteritis: A Systematic Review and Meta-Analysis. Lancet Infect. Dis. 2014, 14, 725–730. [Google Scholar] [CrossRef] [Green Version]
  36. Fang, Y.; Dong, Z.; Liu, Y.; Wang, W.; Hou, M.; Wu, J.; Wang, L.; Zhao, Y. Molecular Epidemiology and Genetic Diversity of Norovirus among Hospitalized Children with Acute Gastroenteritis in Tianjin, China, 2018–2020. BMC Infect. Dis. 2021, 21, 682. [Google Scholar] [CrossRef]
  37. Cao, R.-R.; Ma, X.-Z.; Li, W.-Y.; Wang, B.-N.; Yang, Y.; Wang, H.-R.; Kuang, Y.; You, J.-Z.; Zhao, Z.-Y.; Ren, M.; et al. Epidemiology of Norovirus Gastroenteritis in Hospitalized Children under Five Years Old in Western China, 2015–2019. J. Microbiol. Immunol. Infect. 2021, 54, 918–925. [Google Scholar] [CrossRef] [PubMed]
  38. Mikounou Louya, V.; Nguekeng Tsague, B.; Ntoumi, F.; Vouvoungui, C.; Kobawila, S.C. High Prevalence of Norovirus and Rotavirus Co-infection in Children with Acute Gastroenteritis Hospitalised in Brazzaville, Republic of Congo. Trop. Med. Int. Health 2019, 24, 1427–1433. [Google Scholar] [CrossRef] [PubMed]
  39. Li, L.L.; Liu, N.; Humphries, E.M.; Yu, J.M.; Li, S.; Lindsay, B.R.; Stine, O.C.; Duan, Z.J. Aetiology of Diarrhoeal Disease and Evaluation of Viral–Bacterial Coinfection in Children under 5 Years Old in China: A Matched Case–Control Study. Clin. Microbiol. Infect. 2016, 22, 381.e9–381.e16. [Google Scholar] [CrossRef] [Green Version]
  40. Barsoum, Z. Pediatric Norovirus Gastroenteritis in Ireland: Seasonal Trends, Correlation with Disease Severity, Nosocomial Acquisition and Viral Co-Infection. Indian J. Pediatrics 2020, 88, 463–468. [Google Scholar] [CrossRef]
  41. Rönnelid, Y.; Bonkoungou, I.J.O.; Ouedraogo, N.; Barro, N.; Svensson, L.; Nordgren, J. Norovirus and Rotavirus in Children Hospitalised with Diarrhoea after Rotavirus Vaccine Introduction in Burkina Faso. Epidemiol. Infect. 2020, 148, e245. [Google Scholar] [CrossRef]
  42. Bucardo, F.; Kindberg, E.; Paniagua, M.; Vildevall, M.; Svensson, L. Genetic Susceptibility to Symptomatic Norovirus Infection in Nicaragua. J. Med. Virol. 2009, 81, 728–735. [Google Scholar] [CrossRef]
  43. Mallory, M.; Lindesmith, L.; Graham, R.; Baric, R. GII.4 Human Norovirus: Surveying the Antigenic Landscape. Viruses 2019, 11, 177. [Google Scholar] [CrossRef] [Green Version]
  44. Bucardo, F.; Reyes, Y.; Becker-Dreps, S.; Bowman, N.; Gruber, J.F.; Vinjé, J.; Espinoza, F.; Paniagua, M.; Balmaseda, A.; Svensson, L.; et al. Pediatric Norovirus GII.4 Infections in Nicaragua, 1999–2015. Infect. Genet. Evol. 2017, 55, 305–312. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Ahmed, K.; Dony, J.J.F.; Mori, D.; Haw, L.Y.; Giloi, N.; Jeffree, M.S.; Iha, H. An Outbreak of Gastroenteritis by Emerging Norovirus GII.2[P16] in a Kindergarten in Kota Kinabalu, Malaysian Borneo. Sci. Rep. 2020, 10, 7137. [Google Scholar] [CrossRef] [PubMed]
  46. Wikswo, M.E.; Desai, R.; Edwards, K.M.; Staat, M.A.; Szilagyi, P.G.; Weinberg, G.A.; Curns, A.T.; Lopman, B.; Vinjé, J.; Parashar, U.D.; et al. Clinical Profile of Children with Norovirus Disease in Rotavirus Vaccine Era. Emerg. Infect. Dis. 2013, 19, 1691–1693. [Google Scholar] [CrossRef] [PubMed]
  47. Arowolo, K.O.; Ayolabi, C.I.; Adeleye, I.A.; Lapinski, B.; Santos, J.S.; Raboni, S.M. Molecular Epidemiology of Astrovirus in Children with Gastroenteritis in Southwestern Nigeria. Arch. Virol. 2020, 165, 2461–2469. [Google Scholar] [CrossRef] [PubMed]
  48. Lu, L.; Zhong, H.; Xu, M.; Su, L.; Cao, L.; Jia, R.; Xu, J. Molecular and Epidemiological Characterization of Human Adenovirus and Classic Human Astrovirus in Children with Acute Diarrhea in Shanghai, 2017–2018. BMC Infect. Dis. 2021, 21, 713. [Google Scholar] [CrossRef]
  49. Mozhgani, S.H.R.; Samarbafzadeh, A.R.; Makvandi, M.; Shamsizadeh, A.; Parsanahad, M. Jalilian, S.H. Relative Frequency of Astrovirus in Children Suffering from Gastroenteritis Referred to Aboozar Hospital, Ahvaz. Jundishapur J. Microbiol. 2011, 4, 67–70. [Google Scholar]
  50. Alsuwaidi, A.R.; Al Dhaheri, K.; Al Hamad, S.; George, J.; Ibrahim, J.; Ghatasheh, G.; Issa, M.; Al-Hammadi, S.; Narchi, H. Etiology of Diarrhea by Multiplex Polymerase Chain Reaction among Young Children in the United Arab Emirates: A Case-Control Study. BMC Infect. Dis. 2021, 21, 7. [Google Scholar] [CrossRef]
  51. Moyo, S.J.; Hanevik, K.; Blomberg, B.; Kommedal, O.; Nordbø, S.A.; Maselle, S.; Langeland, N. Prevalence and Molecular Characterisation of Human Adenovirus in Diarrhoeic Children in Tanzania; a Case Control Study. BMC Infect. Dis. 2014, 14, 666. [Google Scholar] [CrossRef]
  52. La Rosa, G.; Della Libera, S.; Petricca, S.; Iaconelli, M.; Donia, D.; Saccucci, P.; Cenko, F.; Xhelilaj, G.; Divizia, M. Genetic Diversity of Human Adenovirus in Children with Acute Gastroenteritis, Albania, 2013–2015. BioMed Res. Int. 2015, 2015, 142912. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Nahar, S.; Akter, T.; Sultana, H.; Akter, A.; Sarkar, O.; Ahmed, M.; Talukder, A.; Ahmed, F.; Dey, S. A Retrospective Analysis of Viral Gastroenteritis in Asia. J. Pediatric Infect. Dis. 2015, 9, 53–65. [Google Scholar] [CrossRef]
  54. Pabbaraju, K.; Tellier, R.; Pang, X.-L.; Xie, J.; Lee, B.E.; Chui, L.; Zhuo, R.; Vanderkooi, O.G.; Ali, S.; Tarr, P.I.; et al. A Clinical Epidemiology and Molecular Attribution Evaluation of Adenoviruses in Pediatric Acute Gastroenteritis: A Case-Control Study. J. Clin. Microbiol. 2020, 59, e02287-20. [Google Scholar] [CrossRef]
  55. Kweon, O.J.; Lim, Y.K.; Kim, H.R.; Kim, T.-H.; Lee, M.-K. Fecal Respiratory Viruses in Acute Viral Respiratory Infection and Nasopharyngeal Diarrheal Viruses in Acute Viral Gastroenteritis: Clinical Impact of Ectopic Viruses Is Questionable. J. Microbiol. Biotechnol. 2018, 28, 465–472. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Santos-Ferreira, N.; Van Dycke, J.; Neyts, J.; Rocha-Pereira, J. Current and Future Antiviral Strategies to Tackle Gastrointestinal Viral Infections. Microorganisms 2021, 9, 1599. [Google Scholar] [CrossRef]
  57. Kajon, A.; Lynch, J., III. Adenovirus: Epidemiology, Global Spread of Novel Serotypes, and Advances in Treatment and Prevention. Semin. Respir. Crit. Care Med. 2016, 37, 586–602. [Google Scholar] [CrossRef] [Green Version]
  58. Balasubramanian, R.; Im, J.; Lee, J.-S.; Jeon, H.J.; Mogeni, O.D.; Kim, J.H.; Rakotozandrindrainy, R.; Baker, S.; Marks, F. The Global Burden and Epidemiology of Invasive Non-Typhoidal Salmonella Infections. Hum. Vaccines Immunother. 2018, 15, 1421–1426. [Google Scholar] [CrossRef]
  59. Pui, C.F.; Wong, W.C.; Chai, L.C.; Tunung, R.; Jyaletchuemi, P.; Noor Hidayah, M.S.; Ubong, A.; Farinazleen, M.G.; Cheah, Y.K.; Son, R. Salmonella: A Foodborne Pathogen. Int. Food Res. J. 2011, 18, 465–473. [Google Scholar]
  60. Chung, N.; Wang, S.-M.; Shen, C.-F.; Kuo, F.-C.; Ho, T.-S.; Hsiung, C.A.; Mu, J.-J.; Wu, F.-T.; Huang, L.-M.; Huang, Y.-C.; et al. Clinical and Epidemiological Characteristics in Hospitalized Young Children with Acute Gastroenteritis in Southern Taiwan: According to Major Pathogens. J. Microbiol. Immunol. Infect. 2017, 50, 915–922. [Google Scholar] [CrossRef]
  61. Wu, L.; Luo, Y.; Shi, G.; Li, Z. Antibiotic Resistance in Nontyphoidal Salmonella Infection. Infect. Drug Resist. 2021, 14, 1403–1413. [Google Scholar] [CrossRef]
  62. Wen, S.C.; Best, E.; Nourse, C. Non-Typhoidal Salmonella Infections in Children: Review of Literature and Recommendations for Management. J. Paediatr. Child Health 2017, 53, 936–941. [Google Scholar] [CrossRef] [PubMed]
  63. Grivas, G.; Lagousi, T.; Mandilara, G. Epidemiological Data, Serovar Distribution and Antimicrobial Resistance Patterns of Salmonella Species in Children, Greece 2011-2017: A Retrospective Study. Acta Med. Acad. 2021, 49, 255. [Google Scholar] [CrossRef] [PubMed]
  64. Barrett, J.; Fhogartaigh, C.N. Bacterial Gastroenteritis. Medicine 2017, 45, 683–689. [Google Scholar] [CrossRef]
  65. Jain, P.; Chowdhury, G.; Samajpati, S.; Basak, S.; Ganai, A.; Samanta, S.; Okamoto, K.; Mukhopadhyay, A.K.; Dutta, S. Characterization of Non-Typhoidal Salmonella Isolates from Children with Acute Gastroenteritis, Kolkata, India, during 2000–2016. Braz. J. Microbiol. 2020, 51, 613–627. [Google Scholar] [CrossRef]
  66. Singh, R.; Yadav, A.S.; Tripathi, V.; Singh, R.P. Antimicrobial Resistance Profile of Salmonella Present in Poultry and Poultry Environment in North India. Food Control 2013, 33, 545–548. [Google Scholar] [CrossRef]
  67. Deng, X.; Ran, L.; Wu, S.; Ke, B.; He, D.; Yang, X.; Zhang, Y.; Ke, C.; Klena, J.D.; Yan, M.; et al. Laboratory-Based Surveillance of Non-Typhoidal Salmonella Infections in Guangdong Province, China. Foodborne Pathog. Dis. 2012, 9, 305–312. [Google Scholar] [CrossRef]
  68. Zhou, Y.; Zhu, X.; Hou, H.; Lu, Y.; Yu, J.; Mao, L.; Mao, L.; Sun, Z. Characteristics of Diarrheagenic Escherichia coli among Children under 5 Years of Age with Acute Diarrhea: A Hospital Based Study. BMC Infect. Dis. 2018, 18, 63. [Google Scholar] [CrossRef] [Green Version]
  69. GebreSilasie, Y.M.; Tullu, K.D.; Yeshanew, A.G. Resistance Pattern and Maternal Knowledge, Attitude and Practices of Suspected Diarrheagenic Escherichia coli among Children under 5 Years of Age in Addis Ababa, Ethiopia: Cross Sectional Study. Antimicrob. Resist. Infect. Control 2018, 7, 110. [Google Scholar] [CrossRef]
  70. Saka, H.K.; Dabo, N.T.; Muhammad, B.; García-Soto, S.; Ugarte-Ruiz, M.; Alvarez, J. Diarrheagenic Escherichia coli Pathotypes From Children Younger Than 5 Years in Kano State, Nigeria. Front. Public Health 2019, 7, 348. [Google Scholar] [CrossRef]
  71. Mare, A.; Man, A.; Toma, F.; Ciurea, C.N.; Coșeriu, R.L.; Vintilă, C.; Maier, A.C. Hemolysin-Producing Strains among Diarrheagenic Escherichia coli Isolated from Children under 2 Years Old with Diarrheal Disease. Pathogens 2020, 9, 1022. [Google Scholar] [CrossRef]
  72. Amisano, G.; Fornasero, S.; Migliaretti, G.; Caramello, S.; Tarasco, V.; Savino, F. Diarrheagenic Escherichia coli in acute gastroenteritis in infants in North-West Italy. New Microbiol. 2011, 34, 45–51. [Google Scholar]
  73. Kargar, M.; Homayoon, M. Prevalence of Shiga Toxins (Stx1, Stx2), EaeA and Hly Genes of Escherichia coli O157:H7 Strains among Children with Acute Gastroenteritis in Southern of Iran. Asian Pac. J. Trop. Med. 2015, 8, 24–28. [Google Scholar] [CrossRef]
  74. Khosravi, A.D. Prevalence of Escherichia coli O157:H7 in Children with Bloody Diarrhea Referring to Abuzar Teaching Hospital, Ahvaz, Iran. J. Clin. Diagn. Res. 2018, 10, 13–15. [Google Scholar] [CrossRef] [PubMed]
  75. Farrokh, C.; Jordan, K.; Auvray, F.; Glass, K.; Oppegaard, H.; Raynaud, S.; Thevenot, D.; Condron, R.; De Reu, K.; Govaris, A.; et al. Review of Shiga-Toxin-Producing Escherichia coli (STEC) and Their Significance in Dairy Production. Int. J. Food Microbiol. 2013, 162, 190–212. [Google Scholar] [CrossRef]
  76. Pérez-Corrales, C.; Leandro-Sandí, K. Diarrheagenic Escherichia coli in Costa Rican Children: A 9-Year Retrospective Study. BMC Res. Notes 2019, 12, 297. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. Shunmugam, P.; Kanapathy, S.; Chan, S.-E.; Singh, K.-K.B. Long-Term Trends in the Epidemiology of Human Enteropathogens in Malaysia. Braz. J. Infect. Dis. 2012, 16, 603–604. [Google Scholar] [CrossRef] [Green Version]
  78. Konaté, A.; Dembélé, R.; Guessennd, N.K.; Kouadio, F.K.; Kouadio, I.K.; Ouattara, M.B.; Kaboré, W.A.D.; Kagambèga, A.; Cissé, H.; Ibrahim, H.B.; et al. Epidemiology and Antibiotic Resistance Phenotypes of Diarrheagenic Escherichia coli Responsible for Infantile Gastroenteritis in Ouagadougou, Burkina Faso. Eur. J. Microbiol. Immunol. 2017, 7, 168–175. [Google Scholar] [CrossRef]
  79. Mahdavi Broujerdi, S.; Roayaei Ardakani, M.; Rezatofighi, S.E. Characterization of Diarrheagenic Escherichia coli Strains Associated with Diarrhea in Children, Khouzestan, Iran. J. Infect. Dev. Ctries. 2018, 12, 649–656. [Google Scholar] [CrossRef]
  80. Celik, T.; Guler, E.; Atas Berksoy, E.; Sorguc, Y.; Arslan, N. Mean Platelet Volume in Children with Acute Gastroenteritis Caused by Entamoeba histolytica. Turk. J. Parasitol. 2015, 39, 205–208. [Google Scholar] [CrossRef]
  81. El-Dib, N.A. Entamoeba histolytica: An Overview. Curr. Trop. Med. Rep. 2017, 4, 11–20. [Google Scholar] [CrossRef]
  82. Ibraheem, F. Etiology and Clinical Manifestations of Infectious Bloody Diarrhea in Children Welfare Teaching Hospital. Iraqi Postgrad. Med. J. 2016, 15, 35–39. [Google Scholar]
  83. Nair, G.; Rebolledo, M.; White, A.C.; Crannell, Z.; Richards-Kortum, R.R.; Pinilla, A.E.; Ramírez, J.D.; López, M.C.; Castellanos-Gonzalez, A. Detection of Entamoeba histolytica by Recombinase Polymerase Amplification. Am. J. Trop. Med. Hyg. 2015, 93, 591–595. [Google Scholar] [CrossRef] [PubMed]
  84. Hegazi, M.A.; Patel, T.A.; El-Deek, B.S. Prevalence and Characters of Entamoeba histolytica Infection in Saudi Infants and Children Admitted with Diarrhea at 2 Main Hospitals at South Jeddah: A Re-Emerging Serious Infection with Unusual Presentation. Braz. J. Infect. Dis. 2013, 17, 32–40. [Google Scholar] [CrossRef] [Green Version]
  85. Naous, A.; Naja, Z.; Zaatari, N.; Kamel, R.; Rajab, M. Intestinal Amebiasis: A Concerning Cause of Acute Gastroenteritis among Hospitalized Lebanese Children. North Am. J. Med. Sci. 2013, 5, 689–698. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  86. Khan, B.; Afshan, K.; Firasat, S.; Qayyum, M. Seroprevalence and Associated Risk Factors of Entamoeba histolytica Infection among Gastroenteritis Patients Visited in Public Healthcare System, Pakistan. J. Pak. Med. Assoc. 2019, 69, 1777–1784. [Google Scholar] [CrossRef] [PubMed]
  87. Enogiomwan, I.E.; Ikponmwosa, E.O.; Chinyere, O.-A.; Christopher, A.B. Evaluation of Vegetable Contamination with Medically Important Helminths and Protozoans in Calabar, Nigeria. J. Adv. Biol. Biotechnol. 2020, 23, 10–16. [Google Scholar] [CrossRef]
  88. Yones, D.; Othman, R.; Hassan, T.; Kotb, S.; Mohamed, A. Prevalence of Gastrointestinal Parasites and its Predictors among Rural Egyptian School Children. J. Egypt. Soc. Parasitol. 2019, 49, 619–630. [Google Scholar] [CrossRef]
  89. Shahrul Anuar, T.; Al-Mekhlafi, H.M.; Abdul Ghani, M.K.; Osman, E.; Mohd Yasin, A.; Nordin, A.; Nor Azreen, S.; Md Salleh, F.; Ghazali, N.; Bernadus, M.; et al. Prevalence and Risk Factors Associated with Entamoeba histolytica/Dispar/Moshkovskii Infection among Three Orang Asli Ethnic Groups in Malaysia. PLoS ONE 2012, 7, e48165. [Google Scholar] [CrossRef] [Green Version]
  90. Maçin, S.; Kaya, F.; Ergüven, S.; Akyön, Y. Akut Gastroenterit Salgınının Mikrobiyolojik Değerlendirmesi. Cukurova Med. J. 2017, 42, 617–622. [Google Scholar] [CrossRef] [Green Version]
  91. Simon Oke, I.A.; Ogunleye, E. Prevalence of Entamoeba histolytica among Primary School Children in Akure, Ondo State, Nigeria. J. Public Health Epidemiol. 2015, 7, 346–351. [Google Scholar] [CrossRef]
  92. Pereira, L.A.; Raboni, S.M.; Nogueira, M.B.; Vidal, L.R.; de Almeida, S.M.; Debur, M.C.; Cruz, C. Rotavirus Infection in a Tertiary Hospital: Laboratory Diagnosis and Impact of Immunization on Pediatric Hospitalization. Braz. J. Infect. Dis. 2011, 15, 215–219. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Gautam, R.; Lyde, F.; Esona, M.D.; Quaye, O.; Bowen, M.D. Comparison of PremierTM Rotaclone®, ProSpecTTM, and RIDASCREEN® Rotavirus Enzyme Immunoassay Kits for Detection of Rotavirus Antigen in Stool Specimens. J. Clin. Virol. 2013, 58, 292–294. [Google Scholar] [CrossRef] [Green Version]
  94. Philip, C.O.; Koech, M.; Kipkemoi, N.; Kirera, R.; Ndonye, J.; Ombogo, A.; Kirui, M.; Kipkirui, E.; Danboise, B.; Hulseberg, C.; et al. Evaluation of the Performance of a Multiplex Reverse Transcription Polymerase Chain Reaction Kit as a Potential Diagnostic and Surveillance Kit for Rotavirus in Kenya. Trop. Dis. Travel Med. Vaccines 2019, 5, 12. [Google Scholar] [CrossRef] [Green Version]
  95. Ha, C.; Yoo, I.Y.; Yun, S.A.; Chung, Y.N.; Huh, H.J.; Lee, N.Y. Performance Evaluation of Automated Fluorescent Immunoassay System ROTA and NORO for Detection of Rotavirus and Norovirus: A Comparative Study of Assay Performance with RIDASCREEN® Rotavirus and Norovirus. J. Clin. Lab. Anal. 2020, 35, e23585. [Google Scholar] [CrossRef]
  96. El-Ageery, S.M.; Ali, R.; Abou El-Khier, N.T.; Rakha, S.A.; Zeid, M.S. Comparison of Enzyme Immunoassay, Latex Agglutination and Polyacrylamide Gel Electrophoresis for Diagnosis of Rotavirus in Children. Egypt. J. Basic Appl. Sci. 2020, 7, 47–52. [Google Scholar] [CrossRef]
  97. Moutelíková, R.; Sauer, P.; Dvořáková Heroldová, M.; Holá, V.; Prodělalová, J. Emergence of Rare Bovine–Human Reassortant DS-1-Like Rotavirus A Strains with G8P[8] Genotype in Human Patients in the Czech Republic. Viruses 2019, 11, 1015. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  98. Gautam, R.; Mijatovic-Rustempasic, S.; Esona, M.D.; Tam, K.I.; Quaye, O.; Bowen, M.D. One-Step Multiplex Real-Time RT-PCR Assay for Detecting and Genotyping Wild-Type Group A Rotavirus Strains and Vaccine Strains (Rotarix® and RotaTeq®) in Stool Samples. PeerJ 2016, 4, e1560. [Google Scholar] [CrossRef] [Green Version]
  99. Norovirus Laboratory Diagnosis. Available online: https://www.cdc.gov/norovirus/lab/diagnosis.html (accessed on 29 September 2021).
  100. Wong, R.S.-L.; Yeo, F.; Chia, W.T.; Lee, C.K.; Leong, M.H.; Ng, C.W.-S.; Poon, K.S.; Yan, G.Z.; Chiu, L.-L.; Yan, B.J.; et al. Performance Evaluation of Cepheid Xpert Norovirus Kit with a User-Modified Protocol. J. Med. Virol. 2017, 90, 485–489. [Google Scholar] [CrossRef]
  101. Gonzalez, M.D.; Langley, L.C.; Buchan, B.W.; Faron, M.L.; Maier, M.; Templeton, K.; Walker, K.; Popowitch, E.B.; Miller, M.B.; Rao, A.; et al. Multicenter Evaluation of the Xpert Norovirus Assay for Detection of Norovirus Genogroups I and II in Fecal Specimens. J. Clin. Microbiol. 2016, 54, 142–147. [Google Scholar] [CrossRef] [Green Version]
  102. Dunbar, N.L.; Bruggink, L.D.; Marshall, J.A. Evaluation of the RIDAGENE Real-Time PCR Assay for the Detection of GI and GII Norovirus. Diagn. Microbiol. Infect. Dis. 2014, 79, 317–321. [Google Scholar] [CrossRef] [PubMed]
  103. Kumthip, K.; Khamrin, P.; Saikruang, W.; Supadej, K.; Ushijima, H.; Maneekarn, N. Comparative Evaluation of Norovirus Infection in Children with Acute Gastroenteritis by Rapid Immunochromatographic Test, RT-PCR and Real-Time RT-PCR. J. Trop. Pediatrics 2017, 63, 468–475. [Google Scholar] [CrossRef]
  104. Jonckheere, S.; Botteldoorn, N.; Vandecandelaere, P.; Frans, J.; Laffut, W.; Coppens, G.; Vankeerberghen, A.; De Beenhouwer, H. Multicenter Evaluation of the Revised RIDA® QUICK Test (N1402) for Rapid Detection of Norovirus in a Diagnostic Laboratory Setting. Diagn. Microbiol. Infect. Dis. 2017, 88, 31–35. [Google Scholar] [CrossRef] [PubMed]
  105. Bruggink, L.D.; Dunbar, N.L.; Marshall, J.A. Evaluation of the Updated RIDA®QUICK (Version N1402) Immunochromatographic Assay for the Detection of Norovirus in Clinical Specimens. J. Virol. Methods 2015, 223, 82–87. [Google Scholar] [CrossRef]
  106. Ranuh, R.G.; Athiyyah, A.F.; Pa, D.A.; Darma, A.; Rahardjo, D.; Shirakawa, T.; Sudarmo, S.M. Assessment of the Rapid Immunochromatographic Test as a Diagnostic Tool for Norovirus Related Diarrhea in Children. Folia Med. Indones. 2019, 55, 48. [Google Scholar] [CrossRef] [Green Version]
  107. Thangjui, S.; Sripirom, N.; Titichoatrattana, S.; Mekmullica, J. Accuracy and Cross-Reactivity of Rapid Diagnostic Tests for Norovirus and Rotavirus in a Real Clinical Setting. Infect. Chemother. 2020, 52, 360. [Google Scholar] [CrossRef]
  108. Geginat, G.; Kaiser, D.; Schrempf, S. Evaluation of Third-Generation ELISA and a Rapid Immunochromatographic Assay for the Detection of Norovirus Infection in Fecal Samples from Inpatients of a German Tertiary Care Hospital. Eur. J. Clin. Microbiol. Infect. Dis. 2011, 31, 733–737. [Google Scholar] [CrossRef] [PubMed]
  109. Kirby, A.; Gurgel, R.Q.; Dove, W.; Vieira, S.C.F.; Cunliffe, N.A.; Cuevas, L.E. An Evaluation of the RIDASCREEN and IDEIA Enzyme Immunoassays and the RIDAQUICK Immunochromatographic Test for the Detection of Norovirus in Faecal Specimens. J. Clin. Virol. 2010, 49, 254–257. [Google Scholar] [CrossRef]
  110. Liu, J.; Kibiki, G.; Maro, V.; Maro, A.; Kumburu, H.; Swai, N.; Taniuchi, M.; Gratz, J.; Toney, D.; Kang, G.; et al. Multiplex Reverse Transcription PCR Luminex Assay for Detection and Quantitation of Viral Agents of Gastroenteritis. J. Clin. Virol. 2011, 50, 308–313. [Google Scholar] [CrossRef] [Green Version]
  111. Yang, B.-Y.; Liu, X.-L.; Wei, Y.-M.; Wang, J.-Q.; He, X.-Q.; Jin, Y.; Wang, Z.-J. Rapid and Sensitive Detection of Human Astrovirus in Water Samples by Loop-Mediated Isothermal Amplification with Hydroxynaphthol Blue Dye. BMC Microbiol. 2014, 14, 38. [Google Scholar] [CrossRef] [Green Version]
  112. Wei, H.; Zeng, J.; Deng, C.; Zheng, C.; Zhang, X.; Ma, D.; Yi, Y. A Novel Method of Real-Time Reverse-Transcription Loop-Mediated Isothermal Amplification Developed for Rapid and Quantitative Detection of Human Astrovirus. J. Virol. Methods 2013, 188, 126–131. [Google Scholar] [CrossRef]
  113. Bonura, F.; Mascarella, C.; Filizzolo, C.; Bonura, C.; Ferraro, D.; Di Bernardo, F.; Collura, A.; Martella, V.; Giammanco, G.M.; De Grazia, S. Evaluation of the Diagnostic Performances of Two Commercially Available Assays for the Detection of Enteric Adenovirus Antigens. Diagn. Microbiol. Infect. Dis. 2021, 101, 115459. [Google Scholar] [CrossRef]
  114. Unal, N.; Yanik, K.; Aydogdu, S.; Eroglu, C.; Gunaydin, M.; Hokelek, M. An Evaluation of Rotavirus and Adenovirus Antigens by the Immunochromatographic Method in Samples with an Initial Diagnosis of Acute Gastroenteritis. Acta Med. Mediterr. 2016, 32, 81–85. [Google Scholar]
  115. Liu, J.; Gratz, J.; Amour, C.; Nshama, R.; Walongo, T.; Maro, A.; Mduma, E.; Platts-Mills, J.; Boisen, N.; Nataro, J.; et al. Optimization of Quantitative PCR Methods for Enteropathogen Detection. PLoS ONE 2016, 11, e0158199. [Google Scholar] [CrossRef] [Green Version]
  116. Liu, J.; Gratz, J.; Amour, C.; Kibiki, G.; Becker, S.; Janaki, L.; Verweij, J.J.; Taniuchi, M.; Sobuz, S.U.; Haque, R.; et al. A Laboratory-Developed TaqMan Array Card for Simultaneous Detection of 19 Enteropathogens. J. Clin. Microbiol. 2012, 51, 472–480. [Google Scholar] [CrossRef] [Green Version]
  117. Meena, B.; Anburajan, L.; Selvaganapathi, K.; Vinithkumar, N.V.; Dharani, G. Characteristics and Dynamics of Salmonella Diversity and Prevalence of Biomarker Genes in Port Blair Bays, South Andaman, India. Mar. Pollut. Bull. 2020, 160, 111582. [Google Scholar] [CrossRef] [PubMed]
  118. Reddington, K.; Tuite, N.; Minogue, E.; Barry, T. A Current Overview of Commercially Available Nucleic Acid Diagnostics Approaches to Detect and Identify Human Gastroenteritis Pathogens. Biomol. Detect. Quantif. 2014, 1, 3–7. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  119. Amjad, M. An Overview of the Molecular Methods in the Diagnosis of Gastrointestinal Infectious Diseases. Int. J. Microbiol. 2020, 2020, 8135724. [Google Scholar] [CrossRef] [PubMed]
  120. Maldonado-Garza, H.J.; Garza-González, E.; Bocanegra-Ibarias, P.; Flores-Treviño, S. Diagnostic Syndromic Multiplex Approaches for Gastrointestinal Infections. Expert Rev. Gastroenterol. Hepatol. 2021, 15, 743–757. [Google Scholar] [CrossRef] [PubMed]
  121. Biswas, J.S.; Al-Ali, A.; Rajput, P.; Smith, D.; Goldenberg, S.D. A Parallel Diagnostic Accuracy Study of Three Molecular Panels for the Detection of Bacterial Gastroenteritis. Eur. J. Clin. Microbiol. Infect. Dis. 2014, 33, 2075–2081. [Google Scholar] [CrossRef]
  122. Zboromyrska, Y.; Vila, J. Advanced PCR-Based Molecular Diagnosis of Gastrointestinal Infections: Challenges and Opportunities. Expert Rev. Mol. Diagn. 2016, 16, 631–640. [Google Scholar] [CrossRef] [PubMed]
  123. Zhang, H.; Morrison, S.; Tang, Y.-W. Multiplex Polymerase Chain Reaction Tests for Detection of Pathogens Associated with Gastroenteritis. Clin. Lab. Med. 2015, 35, 461–486. [Google Scholar] [CrossRef] [Green Version]
  124. Amézquita-López, B.A.; Soto-Beltrán, M.; Lee, B.G.; Yambao, J.C.; Quiñones, B. Isolation, Genotyping and Antimicrobial Resistance of Shiga Toxin-Producing Escherichia coli. J. Microbiol. Immunol. Infect. 2018, 51, 425–434. [Google Scholar] [CrossRef] [PubMed]
  125. Gould, L.H. Update: Recommendations for Diagnosis of Shiga Toxin-Producing Escherichia coli Infections by Clinical Laboratories. Clin. Microbiol. Newsl. 2012, 34, 75–83. [Google Scholar] [CrossRef]
  126. Parsons, B.D.; Zelyas, N.; Berenger, B.M.; Chui, L. Detection, Characterization, and Typing of Shiga Toxin-Producing Escherichia coli. Front. Microbiol. 2016, 7, 478. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  127. Jenkins, C.; Perry, N.T.; Godbole, G.; Gharbia, S. Evaluation of Chromogenic Selective Agar (CHROMagar STEC) for the Direct Detection of Shiga Toxin-Producing Escherichia coli from Faecal Specimens. J. Med. Microbiol. 2020, 69, 487–491. [Google Scholar] [CrossRef] [PubMed]
  128. Hahn, A.; Luetgehetmann, M.; Landt, O.; Schwarz, N.G.; Frickmann, H. Comparison of One Commercial and Two In-House TaqMan Multiplex Real-Time PCR Assays for Detection of Enteropathogenic, Enterotoxigenic and Enteroaggregative Escherichia coli. Trop. Med. Int. Health 2017, 22, 1371–1376. [Google Scholar] [CrossRef] [Green Version]
  129. Khteer Al-Hadraawy, S.; Hussein Abod Al-Khafaji, K.; Deqeem, F.M.; Jawad Kadhim, N. Study Role of Hematological and Leptin Biomarkers in Human Infected with Entamoeba histolytica Parasite. J. Phys. Conf. Ser. 2019, 1294, 062032. [Google Scholar] [CrossRef]
  130. Khteer Al-Hadraawy, S.; AL-Shebly, F.H.; Abood, A.H.; Khadim, N.J. Correlation Study Between Biological Markers In Patients With Entamoeba histolytica Parasite. Biochem. Cell. Arch. 2019, 19, 125–129. [Google Scholar]
  131. Saidin, S.; Yunus, M.H.; Othman, N.; Lim, Y.A.-L.; Mohamed, Z.; Zakaria, N.Z.; Noordin, R. Development and Initial Evaluation of a Lateral Flow Dipstick Test for Antigen Detection Of Entamoeba histolyticain Stool Sample. Pathog. Glob. Health 2017, 111, 128–136. [Google Scholar] [CrossRef] [Green Version]
  132. Mero, S.; Kirveskari, J.; Antikainen, J.; Ursing, J.; Rombo, L.; Kofoed, P.-E.; Kantele, A. Multiplex PCR Detection Of Cryptosporidium sp, Giardia Lamblia and Entamoeba histolytica Directly from Dried Stool Samples from Guinea-Bissauan Children with Diarrhoea. Infect. Dis. 2017, 49, 655–663. [Google Scholar] [CrossRef] [Green Version]
  133. López-Rosas, I.; López-Camarillo, C.; Salinas-Vera, Y.M.; Hernández-de la Cruz, O.N.; Palma-Flores, C.; Chávez-Munguía, B.; Resendis-Antonio, O.; Guillen, N.; Pérez-Plasencia, C.; Álvarez-Sánchez, M.E.; et al. Entamoeba histolytica Up-Regulates MicroRNA-643 to Promote Apoptosis by Targeting XIAP in Human Epithelial Colon Cells. Front. Cell. Infect. Microbiol. 2019, 8, 437. [Google Scholar] [CrossRef]
  134. Lappan, R.; Henry, R.; Chown, S.L.; Luby, S.P.; Higginson, E.E.; Bata, L.; Jirapanjawat, T.; Schang, C.; Openshaw, J.J.; O’Toole, J.; et al. TaqMan Array Cards Enable Monitoring of Diverse Enteric Pathogens across Environmental and Host Reservoirs; Cold Spring Harbor Laboratory: Cold Spring Harbor, NY, USA, 2020. [Google Scholar] [CrossRef]
  135. Fujii, Y.; Doan, Y.H.; Suzuki, Y.; Nakagomi, T.; Nakagomi, O.; Katayama, K. Study of Complete Genome Sequences of Rotavirus A Epidemics and Evolution in Japan in 2012–2014. Front. Microbiol. 2019, 10, 38. [Google Scholar] [CrossRef] [Green Version]
  136. Mohammad, H.A.; Madi, N.M.; Al-Nakib, W. Analysis of Viral Diversity in Stool Samples from Infants and Children with Acute Gastroenteritis in Kuwait Using Metagenomics Approach. Virol. J. 2020, 17, 10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  137. Utsumi, T.; Wahyuni, R.M.; Doan, Y.H.; Dinana, Z.; Soegijanto, S.; Fujii, Y.; Juniastuti; Yamani, L.N.; Matsui, C.; Deng, L.; et al. Equine-like G3 Rotavirus Strains as Predominant Strains among Children in Indonesia in 2015–2016. Infect. Genet. Evol. 2018, 61, 224–228. [Google Scholar] [CrossRef] [Green Version]
  138. Du, H.; Xiong, P.; Ji, F.; Lin, X.; Wang, S.; Zhang, L.; Liu, Y.; Song, Y.; Tao, Z.; Xu, A. Genetic Diversity and Molecular Epidemiological Characterization of Group A Rotaviruses in Raw Sewage in Jinan by next Generation Sequencing. Infect. Genet. Evol. 2021, 91, 104814. [Google Scholar] [CrossRef] [PubMed]
  139. Nakagomi, T.; Doan, Y.H.; Dove, W.; Ngwira, B.; Iturriza-Gómara, M.; Nakagomi, O.; Cunliffe, N.A. G8 Rotaviruses with Conserved Genotype Constellations Detected in Malawi over 10 Years (1997–2007) Display Frequent Gene Reassortment among Strains Co-Circulating in Humans. J. Gen. Virol. 2013, 94, 1273–1295. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  140. Pitkänen, O. Rotavirus Whole Genome Sequencing with Next-Generation Sequencing. Master’s Thesis, Tampere University, Tampere, Finland, 2017. [Google Scholar]
  141. Strubbia, S.; Schaeffer, J.; Besnard, A.; Wacrenier, C.; Le Mennec, C.; Garry, P.; Desdouits, M.; Le Guyader, F.S. Metagenomic to Evaluate Norovirus Genomic Diversity in Oysters: Impact on Hexamer Selection and Targeted Capture-Based Enrichment. Int. J. Food Microbiol. 2020, 323, 108588. [Google Scholar] [CrossRef]
  142. Petronella, N.; Ronholm, J.; Suresh, M.; Harlow, J.; Mykytczuk, O.; Corneau, N.; Bidawid, S.; Nasheri, N. Genetic Characterization of Norovirus GII.4 Variants Circulating in Canada Using a Metagenomic Technique. BMC Infect. Dis. 2018, 18, 521. [Google Scholar] [CrossRef]
  143. Casto, A.M.; Adler, A.L.; Makhsous, N.; Crawford, K.; Qin, X.; Kuypers, J.M.; Huang, M.-L.; Zerr, D.M.; Greninger, A.L. Prospective, Real-Time Metagenomic Sequencing During Norovirus Outbreak Reveals Discrete Transmission Clusters. Clin. Infect. Dis. 2018, 69, 941–948. [Google Scholar] [CrossRef] [Green Version]
  144. Bavelaar, H.H.J.; Rahamat-Langendoen, J.; Niesters, H.G.M.; Zoll, J.; Melchers, W.J.G. Whole Genome Sequencing of Fecal Samples as a Tool for the Diagnosis and Genetic Characterization of Norovirus. J. Clin. Virol. 2015, 70, S98. [Google Scholar] [CrossRef]
  145. Brown, J.R.; Roy, S.; Ruis, C.; Yara Romero, E.; Shah, D.; Williams, R.; Breuer, J. Norovirus Whole-Genome Sequencing by SureSelect Target Enrichment: A Robust and Sensitive Method. J. Clin. Microbiol. 2016, 54, 2530–2537. [Google Scholar] [CrossRef] [Green Version]
  146. Guan, T.-P.; Teng, J.L.L.; Yeong, K.-Y.; You, Z.-Q.; Liu, H.; Wong, S.S.Y.; Lau, S.K.P.; Woo, P.C.Y. Metagenomic Analysis of Sichuan Takin Fecal Sample Viromes Reveals Novel Enterovirus and Astrovirus. Virology 2018, 521, 77–91. [Google Scholar] [CrossRef] [PubMed]
  147. Fernandez-Cassi, X.; Martínez-Puchol, S.; Silva-Sales, M.; Cornejo, T.; Bartolome, R.; Bofill-Mas, S.; Girones, R. Unveiling Viruses Associated with Gastroenteritis Using a Metagenomics Approach. Viruses 2020, 12, 1432. [Google Scholar] [CrossRef] [PubMed]
  148. Tahmasebi, R.; Luchs, A.; Tardy, K.; Hefford, P.M.; Tinker, R.J.; Eilami, O.; de Padua Milagres, F.A.; Brustulin, R.; da Aparecida Rodrigues Teles, M.; dos Santos Morais, V.; et al. Viral Gastroenteritis in Tocantins, Brazil: Characterizing the Diversity of Human Adenovirus F through next-Generation Sequencing and Bioinformatics. J. Gen. Virol. 2020, 101, 1280–1288. [Google Scholar] [CrossRef] [PubMed]
  149. Nakada-Tsukui, K.; Sekizuka, T.; Sato-Ebine, E.; Escueta-de Cadiz, A.; Ji, D.; Tomii, K.; Kuroda, M.; Nozaki, T. AIG1 Affects in Vitro and in Vivo Virulence in Clinical Isolates of Entamoeba histolytica. PLoS Pathog. 2018, 14, e1006882. [Google Scholar] [CrossRef] [Green Version]
  150. Cannoodt, R.; Saelens, W.; Saeys, Y. Computational Methods for Trajectory Inference from Single-Cell Transcriptomics. Eur. J. Immunol. 2016, 46, 2496–2506. [Google Scholar] [CrossRef]
  151. Assisi, C.; Forauer, E.; Oliver, H.F.; Etter, A.J. Genomic and Transcriptomic Analysis of Biofilm Formation in Persistent and Transient Listeria monocytogenes Isolates from the Retail Deli Environment Does Not Yield Insight into Persistence Mechanisms. Foodborne Pathog. Dis. 2021, 18, 179–188. [Google Scholar] [CrossRef]
  152. Lee, H.; Kim, S.I.; Park, S.; Nam, E.; Yoon, H. Understanding Comprehensive Transcriptional Response of Salmonella enterica Spp. in Contact with Cabbage and Napa Cabbage. J. Microbiol. Biotechnol. 2018, 28, 1896–1907. [Google Scholar] [CrossRef] [Green Version]
  153. Segura, A.; Bertoni, M.; Auffret, P.; Klopp, C.; Bouchez, O.; Genthon, C.; Durand, A.; Bertin, Y.; Forano, E. Transcriptomic Analysis Reveals Specific Metabolic Pathways of Enterohemorrhagic Escherichia coli O157:H7 in Bovine Digestive Contents. BMC Genom. 2018, 19, 766. [Google Scholar] [CrossRef] [Green Version]
  154. de OliveiraVieira, K.C.; da Silva, H.R.A.; Rocha, I.P.M.; Barboza, E.; Eller, L.K.W. Foodborne Pathogens in the Omics Era. Crit. Rev. Food Sci. Nutr. 2021, 1–16. [Google Scholar] [CrossRef]
  155. Morsa, D.; Baiwir, D.; La Rocca, R.; Zimmerman, T.A.; Hanozin, E.; Grifnée, E.; Longuespée, R.; Meuwis, M.-A.; Smargiasso, N.; Pauw, E.D.; et al. Multi-Enzymatic Limited Digestion: The Next-Generation Sequencing for Proteomics? J. Proteome Res. 2019, 18, 2501–2513. [Google Scholar] [CrossRef]
  156. Arunima, A.; Yelamanchi, S.D.; Padhi, C.; Jaiswal, S.; Ryan, D.; Gupta, B.; Sathe, G.; Advani, J.; Gowda, H.; Prasad, T.S.K.; et al. “Omics” of Food-Borne Gastroenteritis: Global Proteomic and Mutagenic Analysis OfSalmonella EntericaSerovar Enteritidis. OMICS J. Integr. Biol. 2017, 21, 571–583. [Google Scholar] [CrossRef]
  157. Dallagassa, C.B.; Huergo, L.F.; Stets, M.I.; Pedrosa, F.O.; Souza, E.M.; Cruz, L.M.; Assis, F.E.A.; Wolf, S.; Volanski, W.; Picheth, G.; et al. Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Analysis of Escherichia coli Categories. Genet. Mol. Res. 2014, 13, 716–722. [Google Scholar] [CrossRef]
  158. Rychert, J. Benefits and Limitations of MALDI-TOF Mass Spectrometry for the Identification of Microorganisms. J. Infect. 2019, 2, 1–5. [Google Scholar] [CrossRef]
  159. Chagoyen, M.; Pazos, F. Tools for the Functional Interpretation of Metabolomic Experiments. Brief. Bioinform. 2012, 14, 737–744. [Google Scholar] [CrossRef] [Green Version]
  160. Steiner, D.; Malachová, A.; Sulyok, M.; Krska, R. Challenges and Future Directions in LC-MS-Based Multiclass Method Development for the Quantification of Food Contaminants. Anal. Bioanal. Chem. 2020, 413, 25–34. [Google Scholar] [CrossRef]
  161. Bratburd, J.R.; Keller, C.; Vivas, E.; Gemperline, E.; Li, L.; Rey, F.E.; Currie, C.R. Gut Microbial and Metabolic Responses to Salmonella enterica Serovar Typhimurium and Candida albicans. mBio 2018, 9, e02032-18. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  162. Gallardo, P.; Izquierdo, M.; Vidal, R.M.; Soto, F.; Ossa, J.C.; Farfan, M.J. Gut Microbiota-Metabolome Changes in Children With Diarrhea by Diarrheagenic E. Coli. Front. Cell. Infect. Microbiol. 2020, 10, 485. [Google Scholar] [CrossRef] [PubMed]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Hasan, H.; Nasirudeen, N.A.; Ruzlan, M.A.F.; Mohd Jamil, M.A.; Ismail, N.A.S.; Wahab, A.A.; Ali, A. Acute Infectious Gastroenteritis: The Causative Agents, Omics-Based Detection of Antigens and Novel Biomarkers. Children 2021, 8, 1112. https://doi.org/10.3390/children8121112

AMA Style

Hasan H, Nasirudeen NA, Ruzlan MAF, Mohd Jamil MA, Ismail NAS, Wahab AA, Ali A. Acute Infectious Gastroenteritis: The Causative Agents, Omics-Based Detection of Antigens and Novel Biomarkers. Children. 2021; 8(12):1112. https://doi.org/10.3390/children8121112

Chicago/Turabian Style

Hasan, Haziqah, Nor Ashika Nasirudeen, Muhammad Alif Farhan Ruzlan, Muhammad Aiman Mohd Jamil, Noor Akmal Shareela Ismail, Asrul Abdul Wahab, and Adli Ali. 2021. "Acute Infectious Gastroenteritis: The Causative Agents, Omics-Based Detection of Antigens and Novel Biomarkers" Children 8, no. 12: 1112. https://doi.org/10.3390/children8121112

APA Style

Hasan, H., Nasirudeen, N. A., Ruzlan, M. A. F., Mohd Jamil, M. A., Ismail, N. A. S., Wahab, A. A., & Ali, A. (2021). Acute Infectious Gastroenteritis: The Causative Agents, Omics-Based Detection of Antigens and Novel Biomarkers. Children, 8(12), 1112. https://doi.org/10.3390/children8121112

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop