Correction: Huang et al. A Next Generation Sequencing-Based Protocol for Screening of Variants of Concern in Autism Spectrum Disorder. Cells 2022, 11, 10.

In the original publication [...].

Paraxial mesoderm organoids model development of human somites.

During the development of the vertebrate embryo, segmented structures called somites are periodically formed from the presomitic mesoderm (PSM) and give rise to the vertebral column. While somite formation has been studied in several animal models, it is less clear how well this process is conserved in humans. Recent progress has made it possible to study aspects of human paraxial mesoderm (PM) development such as the human segmentation clock in vitro using human pluripotent stem cells (hPSCs); however, somite formation has not been observed in these monolayer cultures. Here, we describe the generation of human PM organoids from hPSCs (termed Somitoids), which recapitulate the molecular, morphological, and functional features of PM development, including formation of somite-like structures in vitro. Using a quantitative image-based screen, we identify critical parameters such as initial cell number and signaling modulations that reproducibly yielded formation of somite-like structures in our organoid system. In addition, using single-cell RNA-sequencing and 3D imaging, we show that PM organoids both transcriptionally and morphologically resemble their in vivo counterparts and can be differentiated into somite derivatives. Our organoid system is reproducible and scalable, allowing for the systematic and quantitative analysis of human spine development and disease in vitro.

Humans are part of a group of animals called vertebrates, which are all the animals with backbones. Broadly, all vertebrates have a similar body shape with a head at one end and a left and right side that are similar to each other. Although this is not very obvious in humans, vertebrate bodies are derived from pairs of segments arranged from the head to the tail. Each of these segments or somites originates early in embryonic development. Cells from each somite then divide, grow and specialize to form bones such as the vertebrae of the vertebral column, muscles, skin, and other tissues that make up each segment. Studying different animals during embryonic development has provided insights into how somites form and grow, but it is technically difficult to do and only provides an approximate model of how somites develop in humans. Being able to make and study somites using human cells in the lab would help scientists learn more about how somite formation in humans is regulated. Budjan et al. grew human stem cells in the lab as three-dimensional structures called organoids, and used chemical signals similar to the ones produced in the embryo during development to make the cells form somites. Various combinations of signals were tested to find the best way to trigger somite formation. Once the somites formed, Budjan et al. measured them and studied their structure and the genes they used. They found that these lab-grown somites have the same size and structure as natural somites and use many of the same genes. This new organoid model provides a way to study human somite formation and development in the lab for the first time. This can provide insights into the development and evolution of humans and other animals that could then help scientists understand diseases such as the development of abnormal spinal curvature that affects around 1 in 10,000 newborns.

Microbiome-Specific Statistical Modeling Identifies Interplay Between Gastrointestinal Microbiome and Neurobehavioral Outcomes in Patients With Autism: A Case Control Study.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with unclear mechanisms of pathogenesis. Gastrointestinal microbiome alterations were found to correlate with ASD core symptoms, but its specific role in ASD pathogenesis has not been determined. In this study, we used a case-control strategy that simultaneously compared the ASD gastrointestinal microbiome with that from age-sex matched controls and first-degree relative controls, using a statistical framework accounting for confounders such as age. Enterobacteriaceae (including Escherichia/Shigella) and Phyllobacterium were significantly enriched in the ASD group, with their relative abundances all following a pattern of ASD > first degree relative control > healthy control, consistent with our hypothesis of living environment and shared microbial and immunological exposures as key drivers of ASD gastrointestinal microbiome dysbiosis. Using multivariable omnibus testing, we identified clinical factors including ADOS scores, dietary habits, and gastrointestinal symptoms that covary with overall microbiome structure within the ASD cohort. A microbiome-specific multivariate modeling approach (MaAsLin2) demonstrated microbial taxa, such as Lachnoclostridium and Tyzzerella, are significantly associated with ASD core symptoms measured by ADOS. Finally, we identified alterations in predicted biological functions, including tryptophan and tyrosine biosynthesis/metabolism potentially relevant to the pathophysiology of the gut-brain-axis. Overall, our results identified gastrointestinal microbiome signature changes in patients with ASD, highlighted associations between gastrointestinal microbiome and clinical characteristics related to the gut-brain axis and identified contributors to the heterogeneity of gastrointestinal microbiome within the ASD population.

Altered Autonomic Functions and Gut Microbiome in Individuals with Autism Spectrum Disorder (ASD): Implications for Assisting ASD Screening and Diagnosis.

Autism spectrum disorder (ASD) is a complex neurological and developmental disorder, and a growing body of literature suggests the presence of autonomic nervous system (ANS) dysfunction in individuals with ASD. ANS is part of the "gut brain axis", which consists of an intricate interplay between the gut microbiome, mucosal immune system, enteric nervous system, ANS, and central processes receiving input from the vagus nerve. Measurements of the gut microbiome and the autonomic indices can serve as non-invasive markers of the status of the gut-brain axis in ASD. To our knowledge, no previous studies have explored the relationship between ANS and gut microbiome in individuals with ASD. Furthermore, while previous studies investigated the use of autonomic indices and gut microbiome independently as markers of ASD-related comorbidities, such as anxiety, cardiovascular issues, and gastrointestinal dysfunction, the use of combined autonomic indices and gut microbiome factors to classify ASD and control subjects has not been explored. In this study, we characterized autonomic function of a group of individuals with ASD in comparison to their paired, first-degree relative controls. Second, we explored the ASD gut-brain-axis through the relationship between gut microbiome markers and autonomic indices, as well as the correlation between the gut-brain-axis and clinical presentation of ASD. Lastly, this study explores the predictive capability of gut-brain-axis biomarkers (including autonomic and microbiome indices) in subtyping ASD cases, serving as a starting point to investigate the possibility of assisting in ASD screening and diagnosis that still heavily relies on psychological testing, which may be based on highly subjective standards.

A Next Generation Sequencing-Based Protocol for Screening of Variants of Concern in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic influences. There is an increasing demand for ASD genetic testing beyond the traditionally recommended microarray and syndromic autism testing; however, the current whole genome sequencing (WGS) and whole exome sequencing (WES) methods are lacking an academic standard for WGS variant annotation, reporting, and interpretation, tailored towards patients with ASD and offer very limited interpretation for clinical significance. Using WGS data from six family trios, we demonstrate the clinical feasibility and technical implementation of an evidence-based, fully transparent bioinformatics pipeline and report framework for an ASD-focused WGS genetic report. We confirmed a portion of the key variants with Sanger sequencing and provided interpretation with consideration of patients' clinical symptoms and detailed literature review. Furthermore, we showed that identification of the genetic contributions of ASD core symptoms and comorbidities may promote a better understanding of the ASD pathophysiology, lead to early detection of associated comorbidities, and facilitate pharmacologic intervention based on pathological pathways inferred from the genetic information. We will make the bioinformatics pipeline and interpretation framework publicly available, in an easily accessible format, after validation with a larger cohort. We hope that the present proposed protocol can serve as a starting point to invite discourse and debate to further improve approaches in WGS-based genetic consultation for patients with ASD.

Evaluation of Drugs with Therapeutic Potential for Susceptibility of Neisseria Gonorrhoeae Isolates from 8 Provinces in China from 2018.

PURPOSE: The study aimed to evaluate meropenem, fosfomycin, berberine hydrochloride, and doxycycline minimum inhibitory concentrations (MICs) of Neisseria gonorrhoeae collected from eight provinces in China in 2018. METHODS: The MICs of 540 Neisseria gonorrhoeae isolates (451 isolates selected randomly and 89 isolates selected with preference) were determined to meropenem, fosfomycin, berberine hydrochloride, and doxycycline using the agar dilution method, and the MICs of ceftriaxone and azithromycin were detected for comparison. RESULTS: Among 451 randomly selected isolates, the MIC90 was 0.06 mg/L for meropenem, 64 mg/L for fosfomycin, 64 mg/L for berberine hydrochloride, and 16 mg/L for doxycycline. All isolates showed the MIC ≤ 0.125 mg/L to meropenem, 13 isolates (2.9%) showed MIC > 64 mg/L to fosfomycin, 8 isolates (1.8%) demonstrated MIC > 64 mg/L to berberine hydrochloride, and 271 isolates (60.1%) demonstrated MIC > 1 mg/L to doxycycline. Comparing all 540 tested isolates, a correlation of r = 0.50 (P < 0.001) between meropenem and ceftriaxone MIC was observed. In 24 ceftriaxone-decreased susceptibility isolates, all isolates showed an MIC ≤ 0.125 mg/L for meropenem, 1 isolate (4.2%) showed an MIC > 64 mg/L for fosfomycin, 1 isolate (4.2%) showed an MIC > 64 mg/L for berberine hydrochloride, and 13 isolates (54.2%) showed an MIC > 1 mg/L for doxycycline. In 87 azithromycin resistant isolates, all isolates showed an MIC ≤ 0.125 mg/L for meropenem, 2 isolates (2.3%) showed an MIC > 64 mg/L for fosfomycin, 4 isolates (4.6%) showed an MIC > 64 mg/L for berberine hydrochloride, and 64 isolates (73.6%) showed an MIC > 1 mg/L for doxycycline. CONCLUSION: The in vitro results suggest that meropenem might be a promising treatment option for resistant gonococcal infections, while the effects of fosfomycin and berberine hydrochloride should be further evaluated as potential therapeutic agents. The effectiveness of these drugs in animal experiments and clinical use may need further study.

In vitro characterization of the human segmentation clock.

The segmental organization of the vertebral column is established early in embryogenesis, when pairs of somites are rhythmically produced by the presomitic mesoderm (PSM). The tempo of somite formation is controlled by a molecular oscillator known as the segmentation clock1,2. Although this oscillator has been well-characterized in model organisms1,2, whether a similar oscillator exists in humans remains unknown. Genetic analyses of patients with severe spine segmentation defects have implicated several human orthologues of cyclic genes that are associated with the mouse segmentation clock, suggesting that this oscillator might be conserved in humans3. Here we show that human PSM cells derived in vitro-as well as those of the mouse4-recapitulate the oscillations of the segmentation clock. Human PSM cells oscillate with a period two times longer than that of mouse cells (5 h versus 2.5 h), but are similarly regulated by FGF, WNT, Notch and YAP signalling5. Single-cell RNA sequencing reveals that mouse and human PSM cells in vitro follow a developmental trajectory similar to that of mouse PSM in vivo. Furthermore, we demonstrate that FGF signalling controls the phase and period of oscillations, expanding the role of this pathway beyond its classical interpretation in 'clock and wavefront' models1. Our work identifying the human segmentation clock represents an important milestone in understanding human developmental biology.

Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.

Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and explore functional relationships. We performed a genome-wide RNAi screen in human cells and used quantitative descriptors derived from high-throughput imaging to generate multiparametric phenotypic profiles. We show that profiles predicted functions of genes by phenotypic similarity. Specifically, we examined several candidates including the largely uncharacterized gene DONSON, which shared phenotype similarity with known factors of DNA damage response (DDR) and genomic integrity. Experimental evidence supports that DONSON is a novel centrosomal protein required for DDR signalling and genomic integrity. Multiparametric phenotyping by automated imaging and computational annotation is a powerful method for functional discovery and mapping the landscape of phenotypic responses to cellular perturbations.