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Hookworms are soil-transmitted helminths that use immune-evasive strategies to persist in the human duodenum where they are responsible for anemia and protein loss. Given their location and immune regulatory effects, hookworms likely impact the bacterial microbiota. However, microbiota studies struggle to deconvolute the effect of hookworms from confounders such as coinfections and malnutrition. We thus used an experimental human hookworm infection model to explore temporal changes in the gut microbiota before and during hookworm infection. Volunteers were dermally exposed to cumulative dosages of 50, 100 or 150 L3 Necator americanus larvae. Fecal samples were collected for microbiota profiling through 16S rRNA gene amplicon sequencing at weeks zero, four, eight, fourteen and twenty. During the acute infection phase (trial week zero to eight) no changes in bacterial diversity were detected. During the established infection phase (trial week eight to twenty), bacterial richness (Chao1, p = .0174) increased significantly over all volunteers. No relation was found between larval dosage and diversity, stability or relative abundance of individual bacterial taxa. GI symptoms were associated with an unstable microbiota during the first eight weeks and rapid recovery at week twenty. Barnesiella, amongst other taxa, was more abundant in volunteers with more GI symptoms throughout the study. In conclusion, this study showed that clinical GI symptoms following N. americanus infection are associated with temporary microbiota instability and relative abundance of specific bacterial taxa. These results suggest a possible role of hookworm-induced enteritis on microbiota stability.

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BACKGROUND: The microbiome plays an important role in medicine. In psychiatry, it is also useful to examine the microbiome in relation to the pathogenesis and treatment of psychopathology. Nowadays, during consultation, patients and their relatives more frequently ask questions regarding the microbiome, as well as microbiome-based therapies.
AIM: To give an overview of the current knowledge regarding the relationship between microbiome, behaviour and psychiatric disorders in general, and autism in particular.
METHOD: A narrative literature review based on searches in the PubMed and psycinfo databases with the keywords: microbiota, microbiome, microorganisms, mental disorders, psychiatric disorder, autism spectrum disorder, autistic disorder, autistic and autism.
RESULTS: The number of publications concerning the bidirectional relationship between gut microbiota composition and behavior is considerable. The composition of the gut microbiome affects human behavior via subtle, finely regulated, system biological bidirectional influence. Placebo-controlled research into the effects of microbiome interventions is currently limited.
CONCLUSION: It is too early to make definitive statements about the possibilities of diagnosis and therapy aimed at the microbiome in psychiatric disorders. Further scientific research is necessary. How microbiota play a crucial role in host biochemical homeostasis is, however, becoming increasingly clearer.

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When studying the microbiome using next-generation sequencing, the DNA extraction method, sequencing procedures, and bioinformatic processing are crucial to obtain reliable data. Method choice has been demonstrated to strongly affect the final biological interpretation. We assessed the performance of three DNA extraction methods and two bioinformatic pipelines for bacterial microbiota profiling through 16S rRNA gene amplicon sequencing, using positive and negative controls for DNA extraction and sequencing and eight different types of high- or low-biomass samples. Performance was evaluated based on quality control passing, DNA yield, richness, diversity, and compositional profiles. All DNA extraction methods retrieved the theoretical relative bacterial abundance with a maximum 3-fold change, although differences were seen between methods, and library preparation and sequencing induced little variation. Bioinformatic pipelines showed different results for observed richness, but diversity and compositional profiles were comparable. DNA extraction methods were successful for feces and oral swabs, and variation induced by DNA extraction methods was lower than intersubject (biological) variation. For low-biomass samples, a mixture of genera present in negative controls and sample-specific genera, possibly representing biological signal, were observed. We conclude that the tested bioinformatic pipelines perform equally, with pipeline-specific advantages and disadvantages. Two out of three extraction methods performed equally well, while one method was less accurate regarding retrieval of compositional profiles. Lastly, we again demonstrate the importance of including negative controls when analyzing low-bacterial-biomass samples.IMPORTANCE Method choice throughout the workflow of a microbiome study, from sample collection to DNA extraction and sequencing procedures, can greatly affect results. This study evaluated three different DNA extraction methods and two bioinformatic pipelines by including positive and negative controls and various biological specimens. By identifying an optimal combination of DNA extraction method and bioinformatic pipeline use, we hope to contribute to increased methodological consistency in microbiota studies. Our methods were applied not only to commonly studied samples for microbiota analysis, e.g., feces, but also to more rarely studied, low-biomass samples. Microbiota composition profiles of low-biomass samples (e.g., urine and tumor biopsy specimens) were not always distinguishable from negative controls, or showed partial overlap, confirming the importance of including negative controls in microbiota studies, especially when low bacterial biomass is expected.

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The gut microbiome is critical in providing resistance against colonization by exogenous microorganisms. The mechanisms via which the gut microbiota provide colonization resistance (CR) have not been fully elucidated, but they include secretion of antimicrobial products, nutrient competition, support of gut barrier integrity, and bacteriophage deployment. However, bacterial enteric infections are an important cause of disease globally, indicating that microbiota-mediated CR can be disturbed and become ineffective. Changes in microbiota composition, and potential subsequent disruption of CR, can be caused by various drugs, such as antibiotics, proton pump inhibitors, antidiabetics, and antipsychotics, thereby providing opportunities for exogenous pathogens to colonize the gut and ultimately cause infection. In addition, the most prevalent bacterial enteropathogens, including Clostridioides difficile, Salmonella enterica serovar Typhimurium, enterohemorrhagic Escherichia coli, Shigella flexneri, Campylobacter jejuni, Vibrio cholerae, Yersinia enterocolitica, and Listeria monocytogenes, can employ a wide array of mechanisms to overcome colonization resistance. This review aims to summarize current knowledge on how the gut microbiota can mediate colonization resistance against bacterial enteric infection and on how bacterial enteropathogens can overcome this resistance.

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