Baat Gene Knockout Alters Post-Natal Development, the Gut Microbiome, and Reveals Unusual Bile Acids in Mice.

Bile acids (BAs) are steroid detergents in bile that contribute to fat absorption, cell signaling, and microbiome interactions. The final step in their synthesis is amino acid conjugation with either glycine or taurine in the liver by the enzyme bile acid-CoA:amino acid N-acyltransferase (BAAT). Here, we describe the microbial, chemical, and physiological consequences of Baat gene knockout. Baat-/- mice were underweight after weaning but quickly exhibited catch-up growth. At three weeks of age, KO animals had increased phospholipid excretion and decreased subcutaneous fat pad mass, liver mass, glycogen staining in hepatocytes, and hepatic vitamin A stores, but these were less marked in adulthood. Additionally, KO mice had an altered microbiome in early life. Their BA pool was highly enriched in cholic acid but not completely devoid of conjugated BAs. KO animals had 27-fold lower taurine-conjugated BAs than wild type in their liver but similar concentrations of glycine-conjugated BAs and higher microbially conjugated BAs. Furthermore, the BA pool in Baat-/- was enriched in a variety of unusual BAs that were putatively sourced from cysteamine conjugation with subsequent oxidation and methylation of the sulfur group mimicking taurine. Antibiotic treatment of KO mice indicated the microbiome was not the likely source of the unusual conjugations, instead, the unique BAs in KO animals were likely derived from the peroxisomal acyltransferases Acnat1 and Acnat2, which are duplications of Baat in the mouse genome that are inactivated in humans. This study demonstrates that BA conjugation is important for early life development of mice.

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling.

Identification and isolation of contagious individuals along with quarantine of close contacts, is critical for slowing the spread of COVID-19. Large-scale testing in a surveillance or screening capacity for asymptomatic carriers of COVID-19 provides both data on viral spread and the follow-up ability to rapidly test individuals during suspected outbreaks. The COVID-19 early detection program at Michigan State University has been utilizing large-scale testing in a surveillance or screening capacity since fall of 2020. The methods adapted here take advantage of the reliability, large sample volume, and self-collection benefits of saliva, paired with a cost-effective, reagent conserving two-dimensional pooling scheme. The process was designed to be adaptable to supply shortages, with many components of the kits and the assay easily substituted. The processes outlined for collecting and processing SARS-CoV-2 samples can be adapted to test for future viral pathogens reliably expressed in saliva. By providing this blueprint for universities or other organizations, preparedness plans for future viral outbreaks can be developed.

Complex and unexpected outcomes of antibiotic therapy against a polymicrobial infection.

Antibiotics are our primary approach to treating complex infections, yet we have a poor understanding of how these drugs affect microbial communities. To better understand antimicrobial effects on host-associated microbial communities we treated cultured sputum microbiomes from people with cystic fibrosis (pwCF, n = 24) with 11 different antibiotics, supported by theoretical and mathematical modeling-based predictions in a mucus-plugged bronchiole microcosm. Treatment outcomes we identified in vitro that were predicted in silico were: 1) community death, 2) community resistance, 3) pathogen killing, and 4) fermenter killing. However, two outcomes that were not predicted when antibiotics were applied were 5) community profile shifts with little change in total bacterial load (TBL), and 6) increases in TBL. The latter outcome was observed in 17.8% of samples with a TBL increase of greater than 20% and 6.8% of samples with an increase greater than 40%, demonstrating significant increases in community carrying capacity in the presence of an antibiotic. An iteration of the mathematical model showed that TBL increase was due to antibiotic-mediated release of pH-dependent inhibition of pathogens by anaerobe fermentation. These dynamics were verified in vitro when killing of fermenters resulted in a higher community carrying capacity compared to a no antibiotic control. Metagenomic sequencing of sputum samples during antibiotic therapy revealed similar dynamics in clinical samples. This study shows that the complex microbial ecology dictates the outcomes of antibiotic therapy against a polymicrobial infection.

A restructuring of microbiome niche space is associated with Elexacaftor-Tezacaftor-Ivacaftor therapy in the cystic fibrosis lung.

BACKGROUND: Elexacaftor-Tezacaftor-Ivacaftor (ETI) therapy is showing promising efficacy for treatment of cystic fibrosis (CF) and is becoming more widely available since recent FDA approval. However, little is known about how these drugs will affect lung infections, which are the leading cause of morbidity and mortality among people with CF (pwCF). METHODS: We analyzed sputum microbiome and metabolome data from pwCF (n=24) before and after ETI therapy using 16S rRNA gene sequencing and untargeted metabolomics. RESULTS: The sputum microbiome diversity, particularly its evenness, was increased (p=0.036) and the microbiome profiles were different between individuals before and after therapy (PERMANOVA F=1.92, p=0.044). Despite these changes, the microbiomes remained more similar within an individual than across the sampled population. No specific microbial taxa differed in relative abundance before and after therapy, but the collective log-ratio of classic CF pathogens to anaerobes significantly decreased (p=0.013). The sputum metabolome also showed changes associated with ETI (PERMANOVA F=4.22, p=0.002) and was characterized by greater variation across subjects while on treatment. Changes in the metabolome were driven by a decrease in peptides, amino acids, and metabolites from the kynurenine pathway, which were associated with a decrease in CF pathogens. Metabolism of the three small molecules that make up ETI was extensive, including previously uncharacterized structural modifications. CONCLUSIONS: ETI therapy is associated with a changing microbiome and metabolome in airway mucus. This effect was stronger on sputum biochemistry, which may reflect changing niche space for microbial residency in lung mucus as the drug's effects take hold. FUNDING: This project was funded by a National Institute of Allergy and Infectious Disease Grant R01AI145925.

Wheat differential gene expression induced by different races of Puccinia triticina.

Puccinia triticina, the causal agent of wheat leaf rust, causes significant losses in wheat yield and quality each year worldwide. During leaf rust infection, the host plant recognizes numerous molecules, some of which trigger host defenses. Although P. triticina reproduces clonally, there is still variation within the population due to a high mutation frequency, host specificity, and environmental adaptation. This study explores how wheat responds on a gene expression level to different P. triticina races. Six P. triticina races were inoculated onto a susceptible wheat variety and samples were taken at six days post inoculation, just prior to pustule eruption. RNA sequence data identified 63 wheat genes differentially expressed between the six races. A time course, conducted over the first seven days post inoculation, was used to examine the expression pattern of 63 genes during infection. Forty-seven wheat genes were verified to have differential expression. Three common expression patterns were identified. In addition, two genes were associated with race specific gene expression. Differential expression of an ER molecular chaperone gene was associated with races from two different P. triticina lineages. Also, differential expression in an alanine glyoxylate aminotransferase gene was associated with races with virulence shifts for leaf rust resistance genes.

Using transcription of six Puccinia triticina races to identify the effective secretome during infection of wheat.

Wheat leaf rust, caused by the basidiomycete Puccinia triticina, can cause yield losses of up to 20% in wheat producing regions. During infection, the fungus forms haustoria that secrete proteins into the plant cell and effect changes in plant transcription, metabolism, and defense. It is hypothesized that new races emerge as a result of overcoming plant resistance via changes in the secreted effector proteins. To understand gene expression during infection and find genetic differences associated with races, RNA from wheat leaves infected with six different rust races, at 6 days post inoculation, was sequenced using Illumina. As P. triticina is an obligate biotroph, RNA from both the host and fungi were present and separated by alignment to the P. triticina genome and a wheat EST reference. A total of 222,571 rust contigs were assembled from 165 million reads. An examination of the resulting contigs revealed 532 predicted secreted proteins among the transcripts. Of these, 456 were found in all races. Fifteen genes were found with amino acid changes, corresponding to putative avirulence effectors potentially recognized by 11 different leaf rust resistance (Lr) genes. Twelve of the potential avirulence effectors have no homology to known genes. One gene had significant similarity to cerato-platanin, a known fungal elicitor, and another showed similarity to fungal tyrosinase, an enzyme involved in melanin synthesis. Temporal expression profiles were developed for these genes by qRT-PCR and show that the genes expression patterns were consistent between races from infection initiation to just prior to spore eruption.