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Xiao-Ling Zou,1,* Jin-Jie Wu,2,* Hui-Xia Ye,3,* Ding-Yun Feng,1,* Ping Meng,1 Hai-Ling Yang,1 Wen-Bin Wu,1 Hong-Tao Li,1 Zhen He,2 Tian-Tuo Zhang1 1Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, People’s Republic of China; 2Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of China; 3Department of Gynecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Tian-Tuo ZhangDepartment of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, 600 Tianhe Road, Guangzhou, 510630, People’s Republic of ChinaEmail zhtituli@163.comZhen HeDepartment of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510655, Guangdong, People’s Republic of ChinaEmail hezh5@mail.sysu.edu.cnObjective: This study aimed to investigate the gut microbiome profile in different inflammatory phenotypes of treatment-naive newly diagnosed asthmatic adults, to gain insight on the associations between intestinal microbiota and phenotypic features that characterize asthma heterogeneity to develop new treatments for asthma.Methods: Fresh stool samples were obtained from 20 healthy subjects and 47 newly diagnosed asthmatic patients prior to any interventions. The asthmatics were divided into allergic and non-allergic cohorts. Intestinal microbiota was analyzed by 16S rRNA next-generation sequencing. Demographic and clinical parameters were collected. Alpha and beta diversity analysis were calculated to detect differences within sample phylotype richness and evenness between controls and asthmatic patients. Statistically significant differences between samples were analyzed for all used metrics, and features of gut bacterial community structure were evaluated in relation to extensive clinical characteristics of asthmatic patients.Results: Gut microbial compositions were significantly different between asthmatic and healthy groups. Alpha-diversity of the gut microbiome was significantly lower in asthmatics than in controls. The microbiome between allergic and non-allergic asthmatic patients were also different, and 28 differential species were identified. PPAR signaling pathway, carotenoid biosynthesis, and flavonoid biosynthesis were significantly positively correlated with allergy-associated clinical index, including FENO value, blood eosinophil counts, and serum IgE and IL-4 levels. A combination of Ruminococcus bromii, Brevundimonas vesicularis, and Clostridium disporicum showed an AUC of 0.743 in the specific allergic/non-allergic cohort. When integrating C. disporicum, flavone, flavonol biosynthesis, and serum IL-4 values, the AUC achieved 0.929 to classify asthmatics. At the same time, C. colinum and its associated functional pathway exhibited an AUC of 0.78 to distinguish allergic asthmatics from those without allergies.Conclusion: We demonstrated a distinct taxonomic composition of gut microbiota in different asthmatic phenotypes, highlighting their significant relationships. Our study may support considerations of intestinal microbial signatures in delineating asthma phenotypes.Keywords: asthma, phenotypes, gut microbiota, 16S rRNA next-generation sequencing, functional pathway

Novel coronavirus disease-2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an ongoing public-health pandemic worldwide. Although SARS-CoV-2 has been known to spread primarily through respiratory droplets, recent evidence also supports fecal/oral as an additional route of transmission, raising concerns over gastrointestinal (GI) transmission of the infection. Herein, we, as the front-line Chinese GI surgeons, would like to share our experience and lessons in the combat against COVID-19. It is essential to create science-based, rational, and practical strategies during the outbreak of COVID-19. Here, we provide multi-institutional consensus on minimizing disease transmission while continuing to provide care from all aspects for patients in GI surgery, including outpatient clinics, inpatient units, gastrointestinal endoscopy centers, and adjustments in perioperative care. Our experiences and recommendations are worth sharing and may help to establish specific infection-control and outcome measures.

This study was conducted to investigate the effects of soybean antigen proteins on serum cytokine levels and claudin-1 distribution in the intestine of weaned piglets. Seventy piglets (24 d of age) were randomly divided into seven groups. Piglets in group A were fed a basal diet, in groups B, C and D were fed the basal diet supplemented with β-conglycinin; and in groups E, F, G were fed the basal diet supplemented with glycinin. Blood samples were collected and analysed for IFN-γ, IL-2, IL-4 and IL-6 levels on day 24, 26, 28 and 30. At the end of the trial, five piglets per group were sacrificed and the small intestine was collected to evaluate intestinal claudin-1 distribution and OD of the relative staining positivity. β-Conglycinin and glycinin decreased the growth performance in piglets by decreasing ADFI, ADG and increasing F/G. Serum levels of IL-2, IL-4 and IL-6 in β-conglycinin and glycinin groups ranged from 126.067 to 144.067 ng • L−1, 31.798 to 44.360 ng • L−1 and 36.360 to 40.482 ng • L−1 on day 24, 26 and 30. However, serum IFN-γ levels were negatively correlated with soybean antigen proteins supplementation levels ranged from 6.956 to 15.361 ng • L−1. The treatment groups had lower OD values of claudin-1 than those of the control group. The β-conglycinin groups had lower distribution and OD values than the glycinin groups at similar antigen protein supplementation levels. These results suggest that β-conglycinin and glycinin damage the intestinal mucosal immune barrier in weaned piglets.

In this experiment, the effects of soybean antigen proteins on intestinal permeability, 5-hydroxytryptamine (5-HT) levels and secretory IgA (sIgA) distribution in the intestine of weaned piglets were evaluated. Thirty piglets (21 d of age) were randomly divided into three groups: control group, glycinin-sensitised group and β-conglycinin-sensitised group. Piglets in the control group were fed a basal diet, and in two sensitised groups were fed the diet with 4% glycinin or β-conglycinin. Piglets in glycinin and β-conglycinin groups were sensitised twice on 21–27 d and 32–34 d period, respectively. Blood samples were collected and analysed for D-lactic acid, diamine oxidase (DAO) and 5-HT levels on d 21, 28 and 35. At the end of the trial, five piglets per group were sacrificed and the small intestine was collected to evaluate intestinal sIgA distribution and the optical density (OD) of the relative staining positivity. The results revealed that the piglets in glycinin and β-conglycinin groups had higher D-lactic acid, DAO and 5-HT levels than those of the control group (p duodenum > proximal jejunum and distal ileum > distal jejunum. These results suggest that soybean antigen proteins induce allergic reactions, damage the intestinal mucosa, increase intestinal permeability and promote sIgA synthesis in weaned piglets.

In order to generate an antibody against a small hapten molecule, the hapten is cross-linked with carrier protein to make it immunogenic. In this study, the hapten (ochratoxin A, OTA) was coupled to ovalbumin (OVA) by an active ester reaction. To develop a technique for detecting the conjugation, the hapten-protein conjugate (OTA-OVA) was characterized thoroughly by immunoarray technology, ultraviolet (UV) spectroscopy and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), respectively. The molecular weight of OTA-OVA was 50 350.141 Da, and the molecular weight of OVA was 44 887.506 Da, which were determined by MALDI-TOF-MS, respectively. In OTA-OVA, the molecular coupling ratio was 13:1 by MALDI-TOF-MS while the molecular coupling ratio was 10:1 by UV. In this experiment, UV and MALDI-TOF-MS were selected as the efficient methods to evaluate the cross-linking effect and calculate the molecular coupling ratio.