Respiratory pathogens can be spread though the transmission of aerosolised expiratory secretions in the form of droplets or particulates. Understanding the fundamental aerosol parameters that govern how such pathogens survive whilst airborne is essential to understanding and developing methods of restricting their dissemination. Pathogen viability measurements made using Controlled Electrodynamic Levitation and Extraction of Bioaerosol onto Substrate (CELEBS) in tandem with a comparative kinetics electrodynamic balance (CKEDB) measurements allow for a direct comparison between viral viability and evaporation kinetics of the aerosol with a time resolution of seconds. Here, we report the airborne survival of mouse hepatitis virus (MHV) and determine a comparable loss of infectivity in the aerosol phase to our previous observations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Through the addition of clinically relevant concentrations of mucin to the bioaerosol, there is a transient mitigation of the loss of viral infectivity at 40% RH. Increased concentrations of mucin promoted heterogenous phase change during aerosol evaporation, characterised as the formation of inclusions within the host droplet. This research demonstrates the role of mucus in the aerosol phase and its influence on short-term airborne viral stability. Evidence indicates that the coronavirus causing COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can be rapidly spread though the transmission of aerosolised expiratory secretions in the form of droplets or particulates . The phyPrevious research suggests that the evaporative mass flux of water from aerosol containing biological organisms (referred to as bioaerosol below) can dictate ultimate microbial viability outcomes . Oswin e2 concentration (when compared to the high CO2 concentration in the lungs) can be expected to lead to an irreversible partitioning of dissolved CO2 from the droplet into the gas phase [2 leads to an adjustment in the solution phase equilibria with a decrease in bicarbonate anion and H+ ion concentrations, and an increase in the droplet pH. Although the effects of pH on coronavirus stability have been explored in the bulk phase [Respiratory bioaerosol droplets can range from <100 nm to >500 µm diameter ,10 and, as phase ,12. Evaplk phase , the detConsidering the physicochemical processing of respiratory aerosol on exhalation, it is critical to consider the influence of the molecular complexity of respiratory secretions in the study of infectious aerosol. One major component of respiratory secretions commonly hypothesized to affect viral infectivity is mucus ,15,16, aReported here is an exploration of how mucin affects the infectivity of a coronavirus (MHV) in the aerosol phase. This is accomplished through a representative model of respiratory bioaerosol, specifically aerosolized MHV in a mammalian basal cell culture. The working stocks were spiked with clinically relevant concentrations of type II porcine gastric mucin. Type II gastric mucin contains mucin 2 and mucin 6 (MUC2/MUC6), as well MUC5AC ,25,26, aSuspending bioaerosol in an electrodynamic field, using the technique Controlled Electrodynamic Levitation and Extraction of Bioaerosol onto Substrate (CELEBS), allows for the reproducible measurement of viral viability . The Com2 in Dulbecco’s Modified Eagle’s Medium  supplemented with 10% v/v foetal bovine serum , 100 units·mL−1 penicillin , 100 µg·mL−1 streptomycin (Gibco) and 1% v/v L-glutamine (Gibco).Mouse fibroblast cells (17-CL1)  were cul50). The TCID50 was used to calculate the infectious units per mL (u·mL−1) using the Reed and Muench method [7 u·mL−1, Working viral stocks of MHV-A59  were culh method . The pro50 [To determine the short-term effects on aerosolised virus infectivity, aliquots of the MHV working stock were aerosolised and levitated within the CELEBS instrument . A squar50 . A full −1). Temperature was maintained at 19 °C by Peltier cooling of a copper block at the inflow of gas supply to the chamber. RH and temperature measured continuously by a HIH-4062-C  temperature and RH sensor.To measure the effects of RH on virus viability and compare this with similar infectivity studies with SARS-CoV-2, bioaerosol droplets were levitated at 40% and 90% RH. RH was controlled through a mixing ratio of humidified and dry air flow  [w/v) represent MUC5A/MUC5B concentrations in healthy individuals (0.1% w/v) and hypersecretions  associated with smokers and individuals with diseases such as asthma, COPD, and cystic fibrosis [Finally, to investigate the effects of mucin concentrations on viral infectivity, CELEBS measurements were carried out using DMEM (10% FBS) spiked with mucin , where the amount added to the viral working stock was at clinically significant concentrations  . Mucin sfibrosis . A large−4 into basic DMEM, 10% FBS . After a 10-min incubation period, within a sealed tube at room temperature, the samples were diluted back into 5 mL DMEM pH 7.5 to achieve a viral concentration of ~10−6.5; this final dilution was transferred evenly across a 96-well plate containing MHV target 17-CL1 cells. Viral concentrations were predicted from the initial working stock titre and serial dilutions were adapted to achieve ~50% of wells being infected for accurate viral quantification. Initial virus infectivity was calculated from the shortest possible incubation, ≤15 s, and this served as a T = 0 to standardise longer incubations (T = 0 + n). There was no difference in bulk phase pH in solutions of 2% and 10% FBS, To test the effects of pH on viral infectivity, bulk phase infectivity assays were used to control the pH of the solution the MHV virus particles were subjected to. MHV working stocks were diluted to 10t-Test was used to determine if the variance was significant. To compare the effect of two different conditions on viral viability, an F-Test was used to test the null hypothesis that the variances of two populations are equal, if F > F Critical one-tail, the null hypothesis was rejected. Once the variance was determined, a two tailed, a w/v) with measurements made on 100 droplets each for the 5 s period of droplet drying kinetics. Through an analysis of light scattering and particle radius, the time point at which the droplet scatters light consistent with a non-spherical or crystalline particle was identified. Further, the time point at which heterogeneity could be identified in the evaporating droplet was established from a change in scattered light intensity pattern consistent with spontaneous inclusion formation.CKEDB measurements were used to investigate bioaerosol evaporation kinetics and particle phase change. Contrary to CELEBS, a single aerosol droplet of reproducible size  was generated by a DoD  and injected into an electrodynamic balance where it was levitated under environmental conditions measured continuously by RH and temperature probes. The selected RHs and temperature were the same as those studied in the CELEBS infectivity measurements. Each trapped droplet was allowed to equilibrate in line with protocols set out by Rovelli et al. . Capture2 cross sectional area and 50 cm length. RH and temperature were maintained as the droplet fell vertically down the column with aerosol size and morphology measured in line with Hardy et al. [w/v mucin) were subjected to 40% RH and 19 °C and the dried particles were collected on a glass slide at the bottom of the column for scanning electron microscopy (SEM) analysis. Aerosol droplets of a reproducible size were generated using a DoD (the same type used in CELEBS and CKEDB measurements). A continuous stream of uniform droplets was injected into a vertical glass column of 4 cmy et al. . DropletPrior to measurement, samples were coated in graphite. SEM images were obtained using JSM-IT300 (JEOL) at room temperature with an accelerating voltage of 15 kV and a working distance of 9–11 mm. The secondary electron detector (SED) provided topographical information capturing the inelastically scattered electrons from the surface. The backscattered electron detector (BED-C) provided particle phase information capturing the elastically scattered electrons. Sample composition can be inferred from the BED-C images with the scattering proportional to atomic number. Aerosol phase infectivity measurements were used to establish the RH-time dependent loss of infectivity for comparison with that observed for SARS-CoV-2 . At 90% Through increasing the pulse voltage and pulse width applied to the DoD, a 1.8-fold increase in initial bioaerosol volume contributed to a 3.5-fold increase in infectious units per droplet, w/v mucin showed a higher mean infectivity after 30 s levitation compared with 0% mucin (40% RH). Equally, there was a higher mean infectivity in droplets containing 0.3% w/v and 0.5% w/v mucin, w/v mucin. There was no observable effect of mucin on bulk phase viral infectivity, Virus in droplets containing 0.1% In summary, increased concentrations of mucin result in a transient mitigation of viral decay, with significantly higher sustained viral infectivity within the first 2 min of bioaerosol generation. However, this higher infectivity is not apparent at a longer time scale of 5 min for the three mucin concentrations investigated in this study. To explore mechanistically how the presence of mucin affects viral infectivity, we now report the effect of mucin on aerosol phase dynamics.w/v mucin) had two distinct regimes, The representative evaporation profile of a single levitated droplet , there were two distinct regimes during the evaporation. However, there was a change in the scattering pattern towards the end of the initial homogenous evaporation period consistent with the formation of a sphere containing inclusions, Similarly, in a representative evaporation profile for a levitated droplet , w/v mucin. In contrast with increased mucin concentrations, there was an increased proportion of aerosol droplets which showed the formation of inclusions before crystallisation, There was no significant difference in efflorescence time for DMEM droplets without or with mucin  are representative of those respiratory droplets secreted orally through events such as speaking and coughing ,42,43. Dw/v mucin). However, our findings indicate that increased mucin concentrations as a result of respiratory infection may promote viral longevity, temporarily increasing chances of airborne transmission. The CKEDB measurements of consistent evaporation rates between the aerosol of differing mucin concentrations indicate that mucin does not play a significant role in aerosol evaporation kinetics. Instead, mucin spontaneously enhances the formation of inclusions within the droplet which appear to offer protection from deactivation. The viral particle may bind to the inclusions formed during the evaporation of the droplet, thereby shielding the virus from deactivation through the non-physiological conditions inside the equilibrated droplet or particle.There are a multitude of factors that promote or limit airborne transmission between hosts. These factors include, but are not limited to; environmental conditions, viral load, and host intervention strategies ,45. Inve2+ ions, resulting in the formation of larger polymeric structures [Computational modelling from Dommer et al.  supportsructures ,48. SemiMHV enters target cells through a non-sialic acid target mouse carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) ,50. SomeThis research highlights the limitations of using growth media as a sole aerosolisation ingredient and begins to address these limitations, demonstrating a role for mucin in the aerosol phase. Here, harvested virus from infected cells is used as a working MHV stock to aerosolise droplets in the CELEBS. The main component, DMEM basal cell media , is desiThe CELEBS measurements directly coupled airborne viral infectivity measurements with aerosol evaporation phase change dynamics on a high time resolution, allowing for the identification of acute phase change within seconds of droplet generation. This unique feature allows for accurate reporting of relationships between aerosol dynamics and viral infectivity. In conclusion, this research has confirmed the role of RH and phase change on the evaporation kinetics of model respiratory secretions and has established the influence of mucin on internal bioaerosol microphysics. Considered as an ensemble, these factors determine the viability of coronavirus in the aerosol phase.


DEFA1, DEFA5, DEFA7, GIMAP4, GIMAP1, IGLC1, IGLL5, GZMB and HLA) were observed by the CLR and θπ methods. XP-EHH and θπ-ratio revealed that these genes are potentially responsible for coat color (KITLG) and meat quality traits (PDE1B and MYLK2). Furthermore, the heatmap was able to show the clear difference in the haplotype of the KITLG gene between the Kulan hybrids and Asiatic wild ass group and the Guanzhong black donkey group, which is a powerful demonstration of the key role of KITLG in donkey color. Therefore, our study may provide new insights into the genetic basis of coat color, meat quality traits and immunity of Asiatic wild ass and its hybrids.The diversity of livestock coat color results from human positive selection and is an indispensable part of breed registration. As an important biodiversity resource, Asiatic wild ass has many special characteristics, including the most visualized feature, its yellowish-brown coat color, and excellent adaptation. To explore the genetic mechanisms of phenotypic characteristics in Asiatic wild ass and its hybrids, we resequenced the whole genome of one Mongolian Kulan (a subspecies of Asiatic wild ass) and 29 Kulan hybrids (Mongolian Kulan ♂×Xinjiang♀), and the ancestor composition indicated the true lineage of the hybrids. XP-EHH (Cross Population Extended Haplotype Homozygosity), θπ-ratio (Nucleotide Diversity Ratio), CLR (Composite Likelihood Ratio) and θπ (Nucleotide Diversity) methods were used to detect the candidate regions of positive selection in Asiatic wild ass and its hybrids. Several immune genes ( KIT gene plays a vital role in the occurrence of animal coat color, and it is the pigmentary switch in domestic animal species  in wild ass has been reported  and Somali wild ass  (Equus hemionus hemionus) is a kind of subspecies of Asiatic wild ass  , which awild ass , and it wild ass . The Gobwild ass . Kulan iwild ass . They liwild ass . Mongoliwild ass . There iWhole-genome sequencing is an important method to evaluate species population structure and population patterns and identify genome regions related to important economic and environmental adaptation traits. We resequenced the whole genome of Mongolian kulan and 29 Kulan hybrids from Qinghe, Altay region, Xinjiang. The results are expected to fully describe the genomic diversity and population structure of this hybrid population and reveal possible signs of natural or artificial selection. For a meaningful exploration of the formation mechanism of hybrid coat color and other traits, it is necessary to conduct in-depth research.We sampled one Mongolian kulan and 29 Kulan hybrids from the farm of Qinghe Mengyuan Biological Technology Co., LTD.  and extracted genomic DNA from ear tissue by the standard phenol-chloroform protocol . Paired-To determine the ancestry proportion of the Kulan hybrids and their genetic differences to other donkeys , we chosEquus asinus reference assembly EquAsi1.0  using BWA-MEN (http://broadinstitute.github.io/picard), and we used the Genome Analysis Toolkit   was used to obtain functional annotation of the polymorphic sites in all individuals using SNPeff. All the SNPs were counted by effects  and genomic region .After performing quality controls, the cleaned reads were aligned against the  BWA-MEN  with defion 3.8)  to detechttp://tree.bio.ed.ac.uk/software/figtree/). The SNPs data was pruned by PLINK to perform Principal Component Analysis (PCA) and ADMIXTURE analysis. PCA was constructed using the smartPCA program of EIGENSOFT v5.0 (Neighbor-joining (NJ) tree, PCA, and ADMIXTURE methods were used to account for the genetic relationships between Mongolian Kulan ass and the Mongolian Kulan hybrid populations. An unrooted NJ tree based on the matrix of pairwise genetic distances from the autosomal SNP data of 58 donkeys was constructed by PLINK v1.9  with theOFT v5.0 , and ADMOFT v5.0  was usedWe calculated the nucleotide diversity for the 58 individuals with 50 kb windows and 50 kb increments using VCFtools . PopLDdep-values < 0.05 will be considered and given in the supplementary table.To detect selective sweeps in the studied Kulan hybrids, we used Guanzhong donkeys as a reference population, as Guangzhong donkeys are typical Chinese domestic donkeys  and theiIn the present study, 58 whole genomes of donkeys were analyzed. The potential signatures of positive selection between the Kulan hybrids and Guanzhong donkey were evaluated by θπ-ratio and XP-EHH, and CLR and θπ revealed the selection pressure within the Kulan hybrids.A total of 30 resequenced data datasets, including 1 Mongolian kulan and 29 Kulan hybrids , were coBased on the genomic SNPs, we built a neighbor-joining (NJ) tree, principal component analysis and ADMIXTURE . In the Runs of homozygosity (ROHs) can evaluate the inbreeding degree of a population. We identified the length of ROHs into five types: <0.5 Mb, 0.5–1 Mb, 1–2 Mb, 2–4 Mb, and >4 Mb . Long RODEFA1, DEFA5, DEFA7, GIMAP4, GIMAP1, IGLC1, and IGLL5). Numerous studies have shown that these genes play an integral role in the immune response. The hybrid population may have inherited the strong immunity of the Asiatic wild ass against natural pathogens. After enrichment analysis these 77 genes by KOBAS, we obtained 20 significant KEGG pathways when the corrected p-value < 0.05  to find vital KEGG pathways, and there were 11 pathways in the enrichment results  that had strong signals of selection. In addition, previous studies have shown that DEFA1 is crucial for the immunity of horses (GIMAP4 and GIMAP1 belong to the GTP-binding superfamily and to the immunoassociated nucleotide (IAN) subfamily of nucleotide-binding proteins, which are most highly expressed in immune system cells and involved in T/B-cell development and survival . Human Leukocyte Antigen A (HLA) is also called Major Histocompatibility Complex (HMC), which has been proved to be involved in disease resistance in livestock . Coat color is the most visualized feature of Asiatic wild ass and its Kulan hybrids. The coat color of the Kulan hybrids is earthy yellow while the Guanzhong donkey is black. Compared with Guanzhong donkey, KITLG was found in the top 0.5% of regions identified by both methods, then we built a heatmap of haplotypes to verify its true distribution. It was obvious that the Kulan hybrids and other populations had different patterns  and “Regulation of actin cytoskeleton”  were also identified as the relevant terms based on the results of the KEGG enrichment analyses. Interestingly, the “calcium signalling pathway” and“Regulation of actin cytoskeleton” were related to meat quality (PDE1B and MYLK2. Haplotypes based on the SNPs derived from a bacterial artificial chromosome containing the bovine gene PDE1B were associated with traits related to carcass fat (PDE1B (MYLK2 gene was associated with myosin components and may influence muscle development of early porcine embryos through miRNA regulatory network (LCORL gene which was identified by both, the θπ-ratio and XP-EHH methods, as a candidate gene for a selection sweep located on chromosome 3. This gene is known gene to regulate the body size of livestock species (LCORL and donkey body size (LCORL and body size. In any case, as previously said, further deeper analyses could be done on the selection sweeps reported here with the objective of identifying potential causal gene and mutations that could directly explain the selection signals here described.Because the Kulan hybrids that come from Mongolian kulan and Chinese domestic donkeys, we chose Guanzhong donkey as the reference population, which is the representative breed of Chinese domestic donkeys . To undees < 0.05. In the patterns . The KIT species . Further species . Therefo quality  and fromcass fat  and the t (PDE1B . MYLK2 g network . Heteros species , and preody size . XinjianMongolian Kulan is an essential part of Asiatic wild ass, but hunting and deteriorating living conditions have caused their numbers to plummet leading them to nearly the level of a threatened species in the International Union for Conservation of Nature Red list. As donkey genetic resources are being exhausted, breeding planning would help improve and conserve Chinese native donkeys. For this purpose, our results provide a basis for exploring the genomic characteristics of Asiatic wild ass and its Kulan hybrids in relation to crucial economic traits.Based on whole genome re-sequencing data, we provide an overview of Asiatic wild ass and its hybrids. Population genetic structure and genomic diversity analysis identified a new direction for the genetic improvement of Chinese domestic donkeys. Furthermore, we identified genes related to immunity, coat color and meat quality in the Kulan hybrids and the results may serve as valuable resources for research into disease-resistance breeding and the mechanism of animal coat color formation.


Soy yogurt is plant-based dairy of great nutritional interest that is widely accepted in developing countries as a milk alternative. Poor stability has been an urgent problem to solve of soy yogurt products over past several years. The present study aimed to construct multiple network composite gel by adding low acyl gellan gum (LAG) to improve the stability. The effect of addition of LAG on property of soy yogurt was investigated by determining water holding capacity, texture, rheology, particle size, and zeta potential. The results showed that water holding capacity was significantly higher than control. The soy yogurt with 0.1% LAG had a stable gel network with much gel strength and viscosity, and strengthened interaction between complex gel. The addition of LAG increased the particle size and decreased zeta potential. Furthermore, sensory properties were acceptable. Therefore, during industrial production, LAG could act as an appropriate stabilizer to inhibit poor body and bring more desirable sensory characteristics of soy yogurt. Glycine max L. Merr.) are one of the most important leguminous crops in the world and a source of various nutrients for human health including protein, unsaturated fatty acids, vitamins, fiber, and isoflavones [Soybeans  fabricate a binary compound gel using LAG and soy yogurt as a raw material; and (2) explore the effects of different concentrations of LAG on physicochemical , textural, and sensorial properties of soy yogurt. In general, it is expected to provide technical support and theoretical guidance for upgrading soy yogurt products.Lactobacillus plantarum) was obtained from extracts of fermented pickled Chinese cabbage using the previously described method. The strain was precultured with a Mann Rogosa Sharp (MRS) broth culture medium.Low acyl gellan gum was purchased from Sigma-Aldrich Company  with a purity of 98%. Soybeans were a gift from China Agriculture University . Yogurt starter culture (w/w). The LAG solution was prepared by dissolving LAG powder (1 g) into 100 mL of sterile water under a heating condition. Then, 10% Lactobacillus plantarum was incubated in soy milk at the level of 109 CFU/mL at 37 °C for 12 h. The time was determined by the final pH (about 4.0). Then, yogurt samples were stored in a refrigerator at 4 °C.Soybeans were weighed (150 g) and soaked in distilled water overnight at room temperature. Next, the mixture was blended using a mixer for 1 min and then strained to extract the soy milk. Samples were placed in glass jars and pasteurized using a pressure vapor sterilizer at 115 °C for 15 min to prevent lump formation. After cooling to temperature, all jars were treated with LAG solutions . The probe was a 25.4-mm diameter acrylic cylinder. It moved at a velocity of 1 mm/s and a trigger force of 0.05 N. The samples were compressed to 50% of their original height in a double cycle. Three replicates were performed.The rheological measurements were performed using a controlled tension rheometer  method of Cruz et al. . Soy yogThe particle size and zeta potential were performed by dynamic light scattering using NanoBrook90 Plus Zeta  at room temperature. Before measurement, all samples were diluted at 1:200 in distilled water. The effective diameter and zeta potential were automatically calculated by the instrument based on proper sample count rates.Sensorial evaluation was performed using the industry standard . Panelists  were recruited from graduates, being told they were evaluating soy yogurt with different LAG addition in advance. Evaluated attributes were color, elasticity, aroma, chewiness, flavor, and appearance. Each panelist evaluated a 20 mL sample in a white plastic cup coded number randomly. All samples were evaluated in 3 times replication at 4 °C. Sensorial attributes score of <5 were considered as less appealing; scores of 5> by >9 were considered as a boundary on acceptability; scores of 10> by >15 reflect good sensorial quality.Principal component analysis (PCA) is a widely used multivariate analysis technique that can be applied to reduce dimensions by data transformation showing their correlation and trend. PCA applied for soy yogurts were carried out using the following method. The evaluation forms were collected from panelists. Datasets of above stated sensory attributes were put in SPSS 16 software. Through orthogonal transformation, a group of variables that may be correlated are converted into linearly unrelated variables to reduce dimension while maintaining the characteristics that the variance contributes the most. In order to keep original data information integrity, it is essential to find a direction to make the variance of the data projected in this direction largest which contains the most information about the differences in the original data. Therefore, the largest variance value occurred in PC1, the secondary in PC2. PC1 and PC2 are referred to the first principal component factor  and the second principal component factor , respectively. The original data are projected on the plane formed by PC1 and PC2, and represented by two-dimensional data to achieve dimension reduction. The value represents the percentage of data information could be interpreted.p < 0.05).All diagrams were drawn using Origin 8.6 software , and structural formulas were processed by Chem Draw 7.0 software . All indicators were determined at least triplicates, the data were processed by Excel 2010 software . The significant differences were analyzed and evaluated using SPSS 16.0 software  (The water holding capacity (WHC) indicates the gel’s ability to retain the serum that is essential for a fermented product’s quality as it affects consumer acceptability . As showTextural profile analysis (TPA) is an important instrumental technique used to evaluate the textural properties of yogurt by imitating a mouth’s biting or chewing activity . Table 1The soy yogurt exhibited a smaller linear viscoelastic ranging from 0.25% to a 2.78% strain . Under 3The stability of soy yogurt depends mainly on the particle size . ResultsThe distribution of soy yogurt samples as a function of the two principal components extracted by PCA analysis was shown in Soy yogurt, produced bacterial fermentation of soy milk, plays an important role in the present plant-based yogurt alternatives market owing to its high nutritional value and health aspects ,38. The Lactobacillus plantarum) continuously produces lactic acid [Physical properties  are important factors affecting the quality of soy yogurt products. During fermentation, yogurt culture , large amounts of negative charges carried by LAG attract positive charges, resulting in wrapping by protein micelles between LAG, preventing aggregation of protein micelles. The obtained product exhibited a general increase in hardness and viscosity. In addition, soybean proteins, which have been denatured and then solidified into gel in an acidic environment, formed a denser gel network structure and decreased the water precipitation rate of the product with the addition of LAG. Additionally, chewing showed a significant upward trend in a dose-dependent manner. The excellent gel properties might be attributed to formation of a stable and dense network structure, as well as renaturation of the triple helix of LAG, increasing crosslink of junction zones ,48. TsenSoy yogurt is a viscoelastic material, so that the storage (G′) and the loss (G″) modulus were used to test rheological behavior, exploring the evolutionary process of the mixed gels. Heat and sterilization induced protein denaturation resulted in the lowest G’ values of soy milk. Accordingly, the network structure was denser with less porosity. With the concentration of LAG, G′ and G″ are obviously improved. When 0.1% LAG was added to the yogurt sample, the greatest G′ occurred, suggesting solid-like characteristics. The microstructure also suggests that application of LAG resulted in superior stability of soy yogurt. In the colloid system, LAG adsorbed on the soybean protein surface under the electrostatic interaction has thickened the adsorption layer and increased the charge number it could hold . As the Lactobacillus plantarum encapsulation to keep viability under low pH [In this study, the effect of LAG addition on soy yogurt acceptability was analyzed by sensory evaluation. The formation of relatively complex flavor composition of soy yogurt comes from native soybean milk, metabolite of bacterial growth as well as an interaction-produced new compound. Unpleasant perception such as beany flavor is eliminated due to fermentation treatment, accompanied with aroma-related chemicals including acetic acid, 2,3-butanedione, and 2,3-pentanedione 3-hydroxy-2-acetone . Recent r low pH , leadingOur work applied LAG at a proper concentration for the improvement of physicochemical and structural properties of soy yogurt. It not only provides a new choice for overcoming the undesired instability of soy yogurt, but can also be applied for other plant-based yogurts.To study the effect of LAG on the stability of a soy yogurt system, water holding capacity, texture, rheology, particle size and zeta potential were recorded. The addition of LAG at an appropriate concentration improved water holding capacity, gel stiffness and elasticity. Soy yogurts containing LAG were more acceptable in terms of sensory evaluation compared with the control group. Therefore, LAG is recommended as a stabilizer for soy yogurt. The addition of LAG to soy yogurt provided a new choice to improve stability during the production, transportation, and sale of soy yogurt.


Acute promyelocytic leukaemia results from reciprocal translocation between the long arms of chromosomes 15 and 17. This translocation leads to the formation of chimeric gene, which is both the diagnostic marker as well as the therapeutic target of the disease. Additional chromosomal abnormalities are randomly encountered either at diagnosis or during therapy. Here, we present a case of acute promyelocytic leukaemia that had a rare cytogenetic profile at diagnosis.Our patient was a 14‐year‐old boy, who presented with characteristic clinical and morphological features of acute promyelocytic leukaemia. Karyotypic analysis revealed trisomy of chromosome 8 with deletion of 9p in addition to t. The patient passed away within the first 8 h of presentation while receiving conventional chemotherapy and haemodynamic resuscitation.Our patient presented with a rare cytogenetic profile and rapidly progressive disease. According to our extensive literature search, this was the first case of acute promyelocytic leukaemia having pathognomonic t along with trisomy 8 and 9q deletion. ACAadditional chromosomal abnormalitiesAMLacute myeloid leukaemiaAPLacute promyelocytic leukaemiaATRAAl‐trans retinoic acidPMLpromyelocytic leukaemiaRARAretinoic acid receptor alphaRARaretinoic acid receptor alpha1Acute myeloid leukaemia (AML) represents the clonal proliferation of immature precursors of myeloid series in bone marrow and peripheral blood . Variouspromyelocytic leukaemia (PML) gene and cellular differentiation protein; and the retinoid acid receptor alpha (RARA) gene resulting in PML‐RARA fusion gene [PML is a tumour suppressor gene that is transcribed to PML tumour suppressor protein in the cells [RARA gene is transcribed to another transcription factor, the retinoic acid receptor alpha (RARa) protein that plays important role in granulocyte maturation [PML‐RARA is transcribed to the functionally dead PML‐RARa protein with resultant unchecked proliferation and arrested maturation at promyelocyte stage [RARA with other genetic loci that present with disease having similar clinical and haematological features but variable response to chemotherapy [Acute promyelocytic leukaemia (APL) results from reciprocal translocation between chromosomes 15 and 17, t q24;q21) giving rise to chimeric fusion of oncogene; the ion gene . Normal ;q21 giviAdditional chromosomal abnormalities (ACAs) have been reported in APL in association with t15;17) , 7. The  , 7. TheHere, we present a case of APL with trisomy 8 and deletion 9q in association with t, that presented with rapidly fatal aggressive disease.2A 14‐year‐old boy from Faryab province of Afghanistan, presented with pallor, weakness and lethargy that developed over a span of 2 weeks. The patient had also developed bleeding diathesis, including epistaxis, gum bleeding, petechiae and purpurae in the abdomen, chest, upper and lower limbs, 3 days before presentation to the hospital. On examination, the patient was markedly pale, lethargic but alert and orientated. There were numerous foci of petechia and purpura all over the body and subcutaneous haemorrhage at the site of various previous venesection for blood examinations. There were no lymphadenopathy and per‐abdominal examination, the patient had no organomegaly.Blood examination revealed severe normochromic‐normocytic anaemia with severe thrombocytopaenia, as shown in Table 2 of the body per day, and arcenic tri‐oxide (0.15 mg/kg/day) along with haemodynamic resuscitation including packed RBCs, fresh frozen plasma and platelet transfusion.Accordingly, the patient was commenced with prednisolone (1 mg/kg/ day), ATRA, 45 mg/mParents of the patient did not consent for bone marrow examination and therefore blood sample was sent for conventional karyotypic evaluation. Despite the above‐mentioned measures, the patient passed away 8 h after admission. The karyotypic analysis revealed trisomy of chromosome 8 and deletion of 9q in addition to t, as shown in Figure 3PML‐RARA [PML‐RARA chimeric gene and its transcription product, the PML‐RARa protein, are the diagnostic, prognostic as well as therapeutic targets for APL [PML‐RARA, at diagnosis but also during the monitoring of disease, transforming it to be a curable disease [The mechanism underlying the pathogenesis of APL is the reciprocal translocation between the long arms of chromosome 15 and 17 resulting in t and thus the chimeric oncogene PML‐RARA . The PML for APL . Therefo disease .PML‐RARA chimeric gene [RARA gene was persistently being one of the translocation partners [Recent efforts and advancements in cytogenetic and molecular genetic studies revealed that more than 90% of APL cases harboured the typical t15;17) with resultant 5;17 withpartners .ACAs, which are karyotypic abnormalities present in addition to the pathognomonic t, can be encountered in APL patients, either at diagnosis or during therapy . When enThe ACA can be classified as numerical and structural chromosomal abnormalities . In the Our patient presented with rapidly progressive and fatal disease, having typical clinical and morphological features of APL. Chromosomal analysis using conventional karyotypic by Giemsa banding revealed presence of trisomy 8, deletion 9q along with the pathognomonic t. Such karyotypic profile has never been reported elsewhere in the literature. The fact that the patient succumbed in spite of receiving conventional chemotherapy and haemodynamic resuscitation can be a matter of debate and detailed scrutiny. Thus, further multicenter and multinational studies are required for better understanding of the pathogenesis and pathophysiology of APL at molecular levels. This would enable better understanding of additional chromosomal abnormalities and their prognostic implications.4To the best of our knowledge, our patient was the first case of APL to harbour trisomy 8 and deletion 9 in association with t.We would like to extend our very sincere gratitude to Dr. Ahmed Nasir Hanifi and Dr. Jamshid Abdul‐Ghafar, who established the Department of Pathology and Clinical Laboratory at FMIC, Kabul, Afghanistan.Ahmed Maseh Haidary, Sarah Noor, Sahar Noor, Abdul Jamil Rasooli and Ramin Sadat conceived the idea. Ahmed Maseh Haidary, Zeeshan Ansar Ahmed and Sarah Noor were the major contributor to the writing of the manuscript. Maryam Ahmad, Mohammad Sarwar Anwari, Ahmad Shekib Zahier, Abdul Hadi Saqib and Samuel Sharif collected the laboratory data via integrated laboratory management system (ILMS). Ahmed Maseh Haidary, Ahmad Walid Yousufzai and Sarah Noor diagnosed the case. Sahar Noor and Abdul Jamil Rasooli provided the clinical information of the patient. Abdul Hadi Saqib, Maryam Ahmad and Samuel Sharif performed cytogenetic studies. Sarah Noor, Ahmed Maseh Haidary, Abdul Sami Ibrahimkhil, Najla Nasir, Ahmad Shekib Zahier and Haider Ali Malakzai were the major contributors for critically revising the manuscript for important intellectual content. Najla Nasir, Sarah Noor and Ahmed Maseh Haidary have given expert opinion and final approval of the version to be published. All authors read and approved the final manuscript.The authors declare no conflict of interest.


Fusobacterium spp., Porphyromonas and Parvimonas. Uncomplicated appendicitis, however, was characterized by gut-associated microbiomes. Our findings support the hypothesis that two disease types exist in AA, which cannot be distinguished beyond doubt using standard clinical characterization methods or by analysis of the patient’s rectal microbiome. An advanced microbiome diagnosis, however, could improve non-surgical treatment of uncomplicated AA.Mounting evidence suggests that acute appendicitis (AA) is not one but two diseases: complicated appendicitis, which is associated with necrosis leading to perforation or periappendicular abscess, and uncomplicated appendicitis, which does not necessarily result in perforation. Even though AA is the most frequent cause of surgery from abdominal pain, little is known about the origins and etiopathogenesis of this disease, much less regarding the different disease types. In this study, we investigated the microbiome (inter-domain amplicon and metagenome sequencing) of samples from the appendix, rectum and peritoneum of 60 children and adolescents with AA to assess the composition and potential function of bacteria, archaea and fungi. The analysis of the appendix microbial community revealed a shift depending on the severity of the AA. This shift was reflected by two major community state types that represented the complicated and uncomplicated cases. We could demonstrate that complicated, but not uncomplicated, appendicitis is associated with a significant local expansion of oral, bacterial pathogens in the appendix, most strongly influenced by necrotizing  In fact, appendicitis likely represent two different diseases: uncomplicated and complicated appendicitis,9 each with a distinct epidemiology and pathophysiology,10–12 that usually do not develop into the other.14 Complicated appendicitis has been described as perforated appendicitis, periappendicular abscess, or peritonitis, which is defined as an acute inflammation of the peritoneum that occurs in addition to the infection of the appendix.15With approximately 100 cases per 100,000 person-years, acute appendicitis (AA) is the most common reason for emergency abdominal surgery in westernized countries. The lifetime risk of developing AA is estimated at between 6–17%, depending on a person’s sex, life expectancy, region and socioeconomic status.16–22 This claim is supported by the successful treatment of uncomplicated appendicitis with broad-spectrum antibiotics as an alternative to surgery.23 However, as in other gastrointestinal diseases, it is difficult to pinpoint the specific microorganisms that are responsible for the development of appendicitis. One problem is that each “healthy” microbiome is unique and may already include opportunistic pathogens that cause diseases. Another problem is the non-accessibility of healthy appendix microbiomes, as incidental appendectomies are not performed routinely.Recently, mounting evidence suggests that microbial dysbiosis together with an uncontrolled inflammatory response drive the development of the disease.Fusobacterium, Peptostreptococcus, Porphyromonas and Gemella.25 Other studies have connected the inflammation to food-borne pathogens such as Campylobacter jejuni.26 Blood et al.25 have even shown that some of the aforementioned oral pathogens can potentially survive the passage through the stomach, suggesting that AA may be an infectious disease. Out of these oral microorganisms, only Fusobacterium spp. are recurring taxa commonly found in AA,28 with F. nucleatum being capable of infiltrating the appendix lumen depending on the disease severity.27 In contrast to their reportedly high impact in AA, Fusobacteria were only found in 62% of the appendicitis patients described by Swidsinsky et al.27 and, likewise, other pathogens are also inconsistently found among AA patients, suggesting a different/individual etiopathogenesis for AA.Previous work using both culture-dependent and -independent methods suggested the existence of a tight connection between the occurrence and abundance of specific microbial taxa and AA. The latest studies based on amplicon sequencing and real-time quantitative polymerase chain reaction (RT-qPCR) identified a local expansion of oral cavity-associated microbes, including 29 As microbial causes and/or responses may be specific to the grade of disease severity, we prospectively recruited 60 AA patients, grouped them according to postoperative pathological findings and analyzed the microbial composition in the appendix as well as in the peritoneum and rectum (swabs). For this purpose, we performed 16S/23S rRNA gene amplicon sequencing for all samples and shotgun metagenomic analysis of appendix samples. Below, we describe the functional and compositional relevance of bacteria, archaea and fungi with respect to different stages of AA.Only a few studies with a limited number of patients have been carried out to investigate differences in the microbial composition at different stages of AA, and the results were mostly based on amplicon-based analyses.P < .01). Furthermore, the number of patients treated with antibiotics was significantly higher in gangrenous/perforated appendicitis . A total of 20 patients (33%) were administered antibiotics  intravenously before or during surgery, depending on the surgeon’s assessment. We did not expect these antibiotics to affect the microbiome due to the short interval between administration and sampling. Even differences in bacterial beta diversity in relation to antibiotics treatment  are clear confounding factors of the disease severity . Tissue samples of the vermiform appendix and rectal swabs were obtained from 60 patients diagnosed with AA , while peritoneal swabs were taken from 35 of the 60 recruited participants. A full list of samples and respective metadata can be found in Supplementary Table 1. The final evaluation of disease severity and subgrouping of samples was performed based on a histopathological investigation as follows: subacute, catarrhal, phlegmonous, gangrenous and perforated , making it the genus with the highest relative abundance in the appendix samples.We first evaluated the impact of the bacterial microbiome upon disease progression for the three sample types . Based on 16S rRNA gene amplicon sequencing of the V4 region, we identified a total of 2,158 ASVs in the dataset after quality control, filtering and SRS normalization (Supplementary Table 5a-c). All three sample types were dominated by the phyla Firmicutes (see P < .001), we did not observe significant changes in relation to disease severity  opportunistic pathogens show a very low abundance at catarrhal severity (< 1% rel. abundance) and display a successive local expansion upon disease progression. In contrast, the respective abundance of the genera Bacteroides, Ruminococcus gauvreauii group, Collinsella, Coprococcus and CAG-352 (family Ruminococcaceae) was found to be significantly increased in catarrhal appendicitis as compared with higher severity ; however, none of these results remained significant after FDR correction. Thus, we hypothesize that appendectomy has only limited impact on rectal samples. In contrast, peritoneum samples show a high heterogeneity between severity grades, displaying a high abundance of skin-associated microbes  in cases of catarrhal severity and shifting toward a microbial community that resembled the appendiceal microbiome in cases of phlegmonous and gangrenous/perforated severity. The apparent lack of significance of these results may be explained by the low number of catarrhal and phlegmonous samples with detectable bacterial signals .Surprisingly, we did not observe significant microbial differences in rectal and peritoneum samples that were associated with disease severity or any other clinical parameter. In rectal samples, we only observed certain tendencies, such as a successive increase in the genus Methanobrevibacter  and Methanosphaera . Few samples yielded signatures of Methanomethylophilaceae or the thaumarchaeotal families Nitrososphaeraceae and Candidatus Nitrosotenuis, which are believed to represent skin contaminants. We did not observe significant differences between the archaeal composition and disease severity . Interestingly, Methanosphaera abundance and prevalence increased with AA severity, but not significantly .In all sample types, archaeal taxa were dominated by the genera Malassezia restricta represented the most prevalent fungal species that was predominantly found in the non-inflamed and catarrhal appendicitis samples. However, again no significant association between fungal taxa and disease severity or other clinical parameters was observed.In ITS2 gene amplicon sequencing, only 12 appendix samples yielded detectable amounts of fungal signatures after quality control. de novo community state type (CST) clustering based on the abundances of normalized ASV in the bacterial-dominated universal dataset.As mentioned earlier in this communication, AA is hypothesized to comprise two different diseases: complicated appendicitis, which reaches the stage of perforation eventually, and uncomplicated appendicitis, which does not. In many cases, however, it is very difficult or even impossible to assess whether an unperforated appendix would have developed a perforation later on. As we observed a marked shift in the abundance of several bacterial taxa based on disease severity, we further investigated whether the microbial composition could be specific for complicated and uncomplicated appendicitis, respectively. In order to test this hypothesis, we performed a Fusobacterium, Porphyromonas and Parvimonas species . This is also reflected in the number of patients with elevated blood leukocytes: 86.3% of CST 2 patients were diagnosed with leucocytosis but only 57.1% of CST 3 patients (P = .048). However, other diagnostic parameters did not show significant associations with both CSTs, including CRP , PAS (P = .077) and Alvarado score (P = .083). Interestingly, we also observed another cluster of four samples in CST 1. This group is unique as we identified very high abundances of either Haemophilus (rel. abundance of 98.9% and 40.7%) or Escherichia-Shigella (rel. abundance of 28.9% and 53.5%) in the corresponding samples. CST 1 thus represents the “bacterial overgrowth” cluster, in which a single genus or species is hypothesized as being responsible for the AA.Notably, we obtained a total of three different CSTs, two of which correlate well with the proposed disease types . Within  species  which, aFusobacterium necrophorum , Peptostreptococcus stromatis (P = .042) and Solobacterium moorei (P = .042) to be enriched in gangrenous/perforated compared to catarrhal appendicitis. Furthermore, two Porphyromonas species  were also enriched in gangrenous/perforated samples. However, none of the enriched taxa were found to be significantly differently abundant after FDR correction. Such a lack of significant differences was also reported recently by Yuan et al.29 who used a similar classification for AA severity.16S rRNA gene amplicon sequencing provides data about the microbial composition but cannot reliably be used to resolve taxa beyond the genus level or infer the genetic functionality of the microbiome. For this reason, we performed shotgun metagenomic sequencing of all 60 appendix samples and strove to identify key species/subspecies and virulence factors involved in AA pathogenesis. The results of the 16S rRNA gene analysis (Supplementary Table 6a) revealed the species Fusobacterium necrophorum (Padj = .035) was determined in CST 2 as compared to CST 3, further highlighting the importance of Fusobacteria with respect to disease severity. Porphyromonas asaccharolytica was also found to be enriched in CST 2 but not significantly after FDR correction (Padj = .14). This microbial shift was accompanied by an altered abundance of functional genes in the community (Supplementary Table 6b). In particular, we observed a higher abundance of catabolism pathways in CST 2 and especially for amino acids, including lysine fermentation to crotonyl-CoA (Padj = .035), histidine degradation (Padj = .051), glutamate fermentation (Padj = .066) and the associated Na-driven 2-hydroxyglutarate pathway (Padj = .051), as well as the bacterial proteasome pathway (Padj = .051).Again, it is likely that pathological categorization is not necessarily linked to the microbial composition alone, especially for phlegmonous cases. Therefore, we applied the 16S rRNA gene amplicon sequencing-based CST clustering method to our metagenomic data and performed a differential abundance analysis on both the taxonomic and functional levels. Based on MaAsLin2, only a significant enrichment of F. necrophorum was confirmed as being significantly enriched in more complicated cases (CST 2) but also F. nucleatum, two Porphyromonas species  and two unspecified species of the genera Prevotella and Alloprevotella were significantly enriched in CST 2. Despite the marked expansion of those species, no significant change was observed at the functional level. As noted in the MaAsLin2 analysis, an enrichment of catabolic pathways was apparent in CST 2, indicating a potentially increased release of nutrients by, e.g. apoptotic or necrotic host cells. However, this hypothesis is highly speculative and needs to be verified via physiological characterization of the corresponding species.To further validate and test the robustness of the results reported above, DESeq2 was performed . On the Neither the differential abundance nor ABRicate analysis yielded any indications that antimicrobial resistance or virulence genes were enriched among the disease severities.24 This observed shift in diversity is almost exclusively due to changes in bacterial taxa without any significant contribution from fungi or archaea. Both 16S rRNA gene amplicon and metagenomic shotgun sequencing of the appendix microbiome clearly indicate a local expansion of mainly oral cavity-associated microbes in complicated appendicitis, including Fusobacterium, Porphyromonas, Parvimonas, Peptostreptococcus and Solobacterium. Likewise, we could provide support for the previous observation of a stepwise decline in gut-associated Bacteroides as the disease severity increased.28 This decline is accompanied by a substantial reduction in the relative abundance of Ruminococcaceae, Collinsella and Coprococcus from catarrhal to phlegmonous and/or gangrenous/perforated appendicitis . The second cluster was enriched with Fusobacteria and other oral cavity-associated microbes (such as Porphyromonas and Parvimonas), a characteristic which appears to be a hallmark of complicated appendicitis (CST 2). In the third cluster, cases are defined by higher relative abundance of typical gut-associated bacteria such as Bacteroides and Faecalibacterium without an apparent enrichment of oral microbes. These cases might be unlikely to develop perforation and can be attributed to uncomplicated AA. However, while CST 3 and CST 2 clearly separate catarrhal and perforated appendicitis, the phlegmonous and (to a minor extent) gangrenous cases are distributed in both clusters. It is plausible that the microbial community is only partially responsible for AA severity and that some patients may develop complicated appendectomy with a CST-3-like microbial composition. AA is a multifactorial disease that depends on multiple aspects including lifestyle, diet and genetic predisposition.20 It is apparent that proper tissue function and microbial homeostasis require a delicate balance between the immune system, microbiome and host epithelial cells. Previous work by Rivera-Chavez et al.20 for example, indicated that single nucleotide polymorphisms in the IL-6 gene can partially explain the development of complicated appendicitis. Thus, an analysis of the microbiome alone does not allow us to explain the disease etiopathogenesis and an uncomplicated microbial state (CST 3) may still (rarely) lead to gangrene. Due to a lack of longitudinal data, we also cannot exclude the possibility that CSTs can shift from one state to another as the disease progresses. For example, uncomplicated (CST 3) may shift to complicated appendicitis (CST 2) upon the further growth of Fusobacteria and colonization by Porphyromonas and Parvimonas species.For over a decade now, researchers have reported that uncomplicated and complicated appendicitis do not share the same etiopathogenesis. This claim is supported by the observation – among others – that not all cases of AA eventually lead to perforation. While the time span from pain onset to surgery positively correlates with perforation, some cases remain phlegmonous even after a long duration of pain.analysis . We idenPorphyromonas or Parvimonas are present. Fusobacteria are robustly and frequently associated with an increased disease severity and appear to be hallmark taxa in the development of complicated appendicitis. While species of this taxon were also found to be part of the normal appendix microbiota,28 their abundance, prevalence and tissue invasion are greatly increased in complicated appendicitis . As such, F. nucleatum has been shown to induce antimicrobial and pro-inflammatory host responses  and to be capable of actively penetrating and surviving in human tissue and immune cells. Furthermore, Fusobacteria are important biofilm-forming bacteria. Due to the high variety of adhesins they produce, F. nucleatum can bind to host cells, enabling it to act as a docking hub for other microorganisms due to its elongated shape. In colorectal cancer, Fusobacteria frequently co-occur with other oral microbes such as Peptostreptococcus spp. and Leptotrichia spp. and it is feasible that a Fusobacterium-mediated colonization of secondary oral pathogens such as Porphyromonas, Parvimonas, Solobacterium or Peptostreptococcus also occurs in complicated appendicitis.37 All of the mechanisms employed by Fusobacteria are common virulence factors that aid bacteria in establishing new niches, acquiring nutrients and evasion of the immune system.38 As such, the increase in the relative abundance of amino acid metabolizing pathways that was observed in the metagenomic data may be directly linked to the growth of Fusobacteria. Free lysine, histidine, glutamate and serine are required for F. nucleatum growth,39 and the relative abundance of the catabolic pathways for the production of the former three amino acids were enhanced in CST 2. Especially lysine fermentation to crotonyl-CoA was predominantly found to be enriched in more severe cases (CST 2), and this pathway has been described in only few microbes, including F. nucleatum and Porphyromonas gingivalis.40 It is tempting to speculate that Fusobacteria actively trigger apoptosis in intestinal epithelial cells during AA to release peptides and amino acids.The latest and current findings indicate that special attention should be paid to the presence of Fusobacteria in appendicitis patients, especially when other oral pathogens such as ndicitis .27 The prophorum ,27,33 tw41 especially since not enough evidence is available to satisfy Koch’s postulates. The same holds true in case of AA. Fusobacteria are certainly associated with disease severity, and particularly with complicated appendicitis, but we do not yet know whether they play a role as a driver or passenger in the disease.Considering all of these aspects, Fusobacteria appear to play a causative role in several diseases. However, other researchers have also suggested that Fusobacteria only play a passenger role in disease,42 These tools help physicians choose the appropriate therapy and can help to prevent unnecessary surgery. Reliable and easily accessible diagnostic and microbial markers could help to further improve AA diagnosis and even might indicate whether antibiotic treatment is suitable.In recent decades, major improvements in AA diagnosis have been achieved, e.g. by implementing and evaluating standardized clinical scoring systems, such as PAS and Alvarado, or by applying routine imaging techniques to the lower abdomen, including ultrasound or computed tomography.Bulleidia, Dialister and Porphyromonas as compared to healthy controls.24 Longitudinal analyses prior to as well as after appendectomy are required to show whether microbial changes in the distal colon are causally linked with AA.Unfortunately, we did not detect significant differences in the microbiome of rectal samples within our study cohort. The local expansion of opportunistic pathogens within the appendix had no apparent effect on the rectal microbiome. This result may arguably be due to the high diversity of microbes in the large intestine along with a “dilution” of signatures or microbes from the appendix as they pass through the large intestine. Rectal samples are not suitable for distinguishing complicated and uncomplicated appendicitis but may be useful for discriminating between AA and healthy patients or patients with other gastrointestinal diseases that cause abdominal pain, such as colitis. In fact, previous studies have suggested that rectal samples from AA patients show an elevated richness and increase in the abundance of Fusobacteria can be detected both in patients with perforated appendicitis and even in some cases with phlegmonous and gangrenous appendicitis. While the diagnostic value of peritoneal samples is rather low since sampling requires invasive interventions, we could confirm the presence of pathogen signatures in the peritoneal area even in non-perforated appendicitis. The health implications of this finding are uncertain but underline the importance of quick therapeutic intervention in case of AA via surgery or antibiotics.In peritoneal samples, we observed a stepwise but not significant shift from skin-associated taxa dominating in catarrhal cases to intestinal-associated taxa dominating in complicated appendicitis cases. In fact, peritoneal samples may serve as a proxy for AA severity, as invasive pathogens such as 43 the presence of “unknown” microbes in the GIT, such as oral cavity-associated pathogens, may be indicated by increased leukocytes counts.Furthermore, we observed a significantly higher incidence of leucocytosis in complicated as compared to uncomplicated appendicitis cases. While the diagnostic value of white blood cell and leukocyte counts in AA is controversial,27 who postulated that appendicitis is a pathogen-induced infectious disease. This idea was discussed recently in the context of the COVID-19 crisis, as the number of pediatric AA cases substantially dropped (~40%) in 2020 as compared to those in previous years.45 Even though the reasons for this development are unknown, it is possible that social distancing and improved hygiene could have contributed to lower incidence rates by reducing exposure to specific microbes. Furthermore, a recent analysis of stimulated peripheral blood mononuclear cells did not show evidence for innate immune dysfunction in patients with a history in AA, but suggested a possible connection regarding responses between complicated and uncomplicated appendicitis.22 These findings further strengthen the idea that bacterial infection and/or dysbiosis causes AA. In this regard, it is also of crucial importance to trace the origin of the potential pathogens. Recently, the impact of oral microbes in several inflammatory gastrointestinal diseases was highlighted and received an increased amount of attention.47 The history of dental health and oral cavity integrity in AA patients should be investigated in further studies as well, since both factors may show a putative link to appendicitis severity.Several questions regarding the etiopathogenesis of AA are still open. First of all, the origins of appendicitis are still unknown. One possibility was proposed by A. Swidsinsky and his team,AA is a multifactorial disease defined by several host- and microbiome-based factors. Subsequent studies should not be restricted to a singular aspect of this disease, but include holistic analyses of both the host  and microbiome . Considering the potentially negative effects of oral pathogens involved in AA, saliva and subgingival sampling should also be considered in future studies. Whether the tendencies and borderline-significant results we show are truly associated with AA could be further resolved in studies with larger cohorts, ideally including a suitable number of incidental appendectomies that could serve as controls.Fusobacterium infection in appendicitis.We show that uncomplicated AA was characterized rather by the increased relative abundance of typical gastrointestinal microorganisms, whereas complicated AA was associated with misplaced oral microorganisms. Fusobacterium and its associated fatal group are obviously involved in necrotizing activities, which could substantially lead to barrier breaks and perforation. As these microorganisms originate from the oral cavity, their transmission into the gastrointestinal tract needs to be resolved further, including an examination of the function of the stomach barrier or dental issues. Although a reliable microbiome-based biomarker for distinguishing uncomplicated and complicated AA could not be identified in easily-accessible samples in this study, other  parameters could fulfil this requirement. As a consequence, further studies are required to delineate the clinical phenotype of A total of 60 children and adolescents with acute appendicitis (AA) undergoing appendectomy at the Department of Pediatric and Adolescent Surgery at the Medical University of Graz from April to June 2019 were prospectively recruited. The study was approved by the Ethics committee of the Medical University in Graz (31–004 ex 18/19) and performed according to the Helsinki Declaration. Written informed consent was given by the participants and/or the caregivers after they were provided with written and oral information about the study. All data and samples were pseudo-anonymized.49Preoperatively, demographic data and serum parameters were obtained, including total leukocyte count and C-reactive protein (CRP). Additionally, the Alvarado score and Pediatric Appendicitis Score (PAS) were assessed.n = 60) and in cases of fluid collection in the abdominal cavity peritoneal swabs (n = 34) were taken with sterile nylon swabs  prior to and during the operation, respectively. After the removal of the vermiform appendix, about 1 cm of the proximal part was excised and stored at −80°C together with the other samples until further processing. The remaining tissue was used for standard histological examination. According to Carr,5 catarrhal appendicitis was defined as a local inflammation with few intraepithelial neutrophils and reactive intraepithelial changes. Phlegmonous appendicitis was diagnosed in cases with evidence of neutrophils invading the mucosa, submucosa and muscularis propria, intraluminal abscess and invasion of the surrounding tissue. Gangrenous appendicitis additionally showed intramural necrosis. Perforation was defined as microscopic or macroscopic perforation in the abdominal cavity. Sample information can be accessed in the Supplementary Table 1.Rectal  according to manufacturer’s instructions with the following exception: Lysis and homogenization of the samples was performed in two cycles of bead beating using a MagNA Lyser (Roche Diagnostics GmbH) at 6500 rpm for 30s with intermediate cooling. The DNA concentration was measured using the Qubit™ dsDNA HS Assay Kit (ThermoFisher Scientific).50 We performed a nested PCR to specifically amplify archaea DNA by using the primer combination 344 F-1041 R/Illu519F-Illu806R as described previously.52 PCR reactions were carried out in a final volume of 25 µL containing: TAKARA Ex Taq® buffer with MgCl2 , primers (200 nM of each), dNTP mix (200 µM of each), TAKARA Ex Taq® Polymerase 0.5 U, water  and DNA template (1–2 µL of genomic DNA). To amplify DNA from fungal specimens, we used the primer pair ITS86F-ITS4 containing Illumina adapter sequences.53 The PCR reaction was carried out with the same setup as described above, but 400 nM of each primer were used instead. All primers and PCR conditions used are listed in Supplementary Tables 2 and 3.To identify the microbial communities from the appendix, rectum and peritoneum, we amplified the V4 region of the 16S rRNA gene to detect bacteria and archaea and the internal transcribed spacer 2 (ITS2) region of the 23S rRNA gene to detect fungi. Sequences from prokaryotic specimens were amplified with the universal primer pair 515 F and 806 R containing Illumina adapter sequences.Both the library preparation and sequencing of the amplicons were performed at the Core Facility Molecular Biology, Center for Medical Research at the Medical University Graz, Austria. In brief, SequalPrep™ normalization plates (Invitrogen) were used to normalize the DNA concentration, and each sample was subsequently indexed with a unique barcode sequence (8 cycles index PCR). All indexed samples were pooled, and the products of the indexing PCR were purified with gel electrophoresis. Sequencing was performed using an Illumina MiSeq device and the MS-102-3003 MiSeq® Reagent Kit v3-600 cycles (2x251 cycles).55 Briefly, the DADA2 algorithm was used to demultiplex and de-noise truncated reads as well as to generate amplicon sequence variants (ASVs).56 Taxonomic assignment was based on the SILVA v138 database for prokaryotic specimens and on the UNITE v8.3 database for fungi.58 Fungal raw reads were also pre-processed with ITSxpress,59 trimming reads to the desired ITS2 region. The datasets were filtered as follows: Potential contaminants were identified and removed with the R software package decontam by providing negative controls (DNA extraction and PCR negative controls) and applying a threshold of 0.25.60 Control samples were subsequently removed from the dataset. Unassigned ASVs, those classified as chloroplast and mitochondria, and ASVs with fewer than 10 total reads were also removed. Rarefaction of the datasets was performed by scaling with ranked subsampling (SRS) using rarefaction depths of 1000, 100 and 50 for bacteria, fungi and archaea, respectively.61The MiSeq data for all three approaches  were analyzed individually using QIIME2 V2019.11 as described previously.Shotgun metagenome sequencing was performed for all 60 appendix samples. A total of 200 ng of extracted DNA from each sample was sent to Macrogen Europe . Library extraction was performed with the TruSeq DNA PCR-Free kit (Illumina) and sequenced with the Illumina NovaSeq 6000 platform (Illumina).54 In brief, quality control and filtering were performed with fastqc (v0.11.8) and trimmomatic (v0.38).63 Accepted reads were mapped to the human chromosome hg19 with bowtie2 (v2.3.5),64 and unmapped reads were retained using samtools (v1.9).65 Bedtools (v2.29.0) was subsequently used to extract host-removed files.66 Unfortunately, a genome-centric approach was not possible for this dataset, as the assembly with Megahit (v1.1.3) and the subsequent binning using MaxBin (v2.2.4) did not yield any draft genomes.68 Even though all samples had ~20 Mil. raw reads, about 99% of all reads mapped to the human genome. This high abundance of host reads could not be mitigated by using the NEBNext® Microbiome DNA Enrichment Kit in our approach. Instead, we performed a gene-centric analysis, performing blastx with diamond (v2.0.8) to annotate the host-removed, quality-filtered reads against the NCBI nr database (release Sep. 2020).69 Megan (6.18.0) was used to remove reads that were classified as Metazoa and to compare samples based on normalized counts.70 Subsequently, the taxonomic and functional annotation based on the SEED database was exported and used for statistical analysis.71Raw reads were processed as described previously.72 Furthermore, we mapped the quality filtered contigs against the genome of Fusobacterium nucleatum (NCBI Reference Sequence: NZ_LN831027.1) and several archaeal genomes, using species that were repeatedly reported to be associated to the human gut, including Methanobrevibacter smithii (DSM 2374 and strain WWM1085), Methanosphaera stadtmanae (DSM 3091), Methanomassiliicoccus luminyensis (B10), Methanocorpusculum, Methanobacterium, Halorubrum lipolyticum (DSM 21995) and Haloferax sp. Arc-Hr.73In addition, contigs were screened for antimicrobial resistance and virulence genes with ABRicate using all available databases: ARG-ANNOT, CARD, EcOH, Ecoli_VF, MEGARES 2.00, NCBI AMRFinderPlus, PlasmidFinder, Resfinder and VFDB.Statistical analysis of clinical parameters was performed using the IBM® SPSS® Statistics 26 software package. After testing for Gaussian normal distribution using the Shapiro-Wilk test, Kruskal-Wallis tests were applied to nonparametric data, while the comparison of parametric data was conducted with a one-way analysis of variance (ANOVA) and a Tukey post-hoc test. Comparisons of categorical data were performed with the chi-square test.74 Biplots were performed based on the weighted UniFrac distance matrix and were calculated using the biplot plugin in QIIME2. The Emperor plugin was used to illustrate the results of the biplot analysis.76Microbial data analysis and visualization were done with QIIME2 (V2019.11) and R (V4.1.1). Phylogenetic distances for the amplicon sequencing data were calculated in QIIME2 using the fasttree plugin and subsequently analyzed following the core-metrics-phylogenetic command without further subsampling.77 ggplot2,78 Maaslin2,79 DESeq2.80 A full list of all packages and versions used can be found in Supplementary Table 4. Alpha diversity was calculated based on the filtered and normalized dataset, and mean values ± standard deviation (SD) are reported. After testing for normality, pairwise Wilcoxon signed-rank tests were performed, and the resulting P-values were corrected for false discovery rates (FDR) according to Benjamini and Hochberg.81 For MaAsLin2, the default settings were applied except for max_significance = 0.05 and min_prevalence = 0.001. DESeq2 analysis was considered significant if Padj < 0.05 and log2FoldChange ≥ 0.58 (corresponds to a 1.5-fold change).Differential abundance and alpha diversity testing as well as visualization were performed using normalized data within R and the packages phyloseq,de novo community state type (CST) clustering based on rarefied 16S rRNA gene data  and the corresponding weighted UniFrac distance matrix. Calculation of the CSTs was applied using the methodology of DiGiulio et al.82 Based on gap statistics, the number of clusters was determined (k = 3).We performed Click here for additional data file.