Proteomic Profiling of Hindlimb Skeletal Muscle Disuse in a Murine Model of Sepsis.

CONTEXT: Sepsis leads to multiple organ dysfunction and negatively impacts patient outcomes. Skeletal muscle disuse is a significant comorbidity in septic patients during their ICU stay due to prolonged immobilization. HYPOTHESIS: Combination of sepsis and muscle disuse will promote a unique proteomic signature in skeletal muscle in comparison to disuse and sepsis separately. METHODS AND MODELS: Following cecal ligation and puncture (CLP) or Sham surgeries, mice were subjected to hindlimb suspension (HLS) or maintained normal ambulation (NA). Tibialis anterior muscles from 24 C57BL6/J male mice were harvested for proteomic analysis. Proteomic profiles were assessed using nano-liquid chromatography with tandem mass spectrometry, followed by data analysis including Partial Least Squares Discriminant Analysis (PLS-DA), to compare the differential protein expression across groups. RESULTS: A total of 2876 differentially expressed proteins were identified, with marked differences between groups. In mice subjected to CLP and HLS combined, there was a distinctive proteomic signature characterized by a significant decrease in the expression of proteins involved in mitochondrial function and muscle metabolism, alongside a marked increase in proteins related to muscle degradation pathways. The PLS-DA demonstrated a clear separation among experimental groups, highlighting the unique profile of the CLP/HLS group. This suggests an important interaction between sepsis-induced inflammation and disuse atrophy mechanisms in sepsis-induced myopathy. INTERPRETATIONS AND CONCLUSIONS: Our findings reveal a complex proteomic landscape in skeletal muscle exposed to sepsis and disuse, consistent with an exacerbation of muscle protein degradation under these combined stressors. The identified proteins and their roles in cellular stress responses and muscle pathology provide potential targets for intervention to mitigate muscle dysfunction in septic conditions, highlighting the importance of addressing both sepsis and disuse concurrently in clinical and experimental settings.

Can dietary magnesium sources and buffer change the ruminal microbiota composition and fermentation of lactating dairy cows?

Magnesium oxide (MgO) is one of the most used Mg supplements in livestock. However, to avoid relying upon only one Mg source, it is important to have alternative Mg sources. Therefore, the objective of this study was to evaluate the effects of the interaction of two Mg sources with buffer use on the ruminal microbiota composition, ruminal fermentation, and nutrient digestibility in lactating dairy cows. Twenty lactating Holstein cows were blocked by parity and days in milk into five blocks with four cows each, in a 2 × 2 factorial design. Within blocks, cows were assigned to one of four treatments: 1) MgO; 2) MgO + Na sesquicarbonate (MgO+); 3) calcium-magnesium hydroxide (CaMgOH); 4) CaMgOH + Na sesquicarbonate (CaMgOH+). For 60 d, cows were individually fed a corn silage-based diet, and treatments were top-dressed. Ruminal fluid was collected via an orogastric tube, for analyses of the microbiota composition, volatile fatty acids (VFA), lactate, and ammonia nitrogen (NH3-N). The microbiota composition was analyzed using V4/16S rRNA gene sequencing, and taxonomy was assigned using the Silva database. Statistical analysis was carried out following the procedures of block design analysis, where block and cow were considered random variables. Effects of Mg source, buffer, and the interaction between Mg Source × Buffer were analyzed through orthogonal contrasts. There was no interaction effect of the two factors evaluated. There was a greater concentration of NH3-N, lactate, and butyrate in the ruminal fluid of cows fed with CaMg(OH)2, regardless of the buffer use. The increase in these fermentation intermediates/ end-products can be explained by an increase in abundance of micro-organisms of the genus Prevotella, Lactobacillus, and Butyrivibrio, which are micro-organisms mainly responsible for proteolysis, lactate-production, and butyrate-production in the rumen, respectively. Also, dietary buffer use did not affect the ruminal fermentation metabolites and pH; however, an improvement of the apparent total tract digestibility of dry matter (DM), organic matter (OM), neutral fiber detergent (NDF), and acid fiber detergent (ADF) were found for animals fed with dietary buffer. In summary, there was no interaction effect of buffer use and Mg source, whereas buffer improved total tract apparent digestibility of DM and OM through an increase in NDF and ADF digestibility and CaMg(OH)2 increased ruminal concentration of butyrate and abundance of butyrate-producing bacteria.

Magnesium oxide (MgO) is extensively used as a dietary magnesium (Mg) source in dairy cow diets. However, dairy operations can benefit from other Mg sources. Thus, we evaluated the replacement of dietary MgO with calcium­magnesium hydroxide (CaMg(OH)2) in diets with and without ruminal buffer and their effects on the ruminal microbiota composition, ruminal fermentation, and nutrient digestibility in lactating dairy cows. The study used 20 lactating Holstein cows that were blocked in groups of four and randomly assigned to one of the four treatments. The ruminal content, feed, feces, and urine were collected for analysis of the microbiota composition, ruminal fermentation, nitrogen metabolism, and apparent nutrient digestibility. There was no interaction effect of dietary buffer use and Mg source, while buffer improved total tract apparent digestibility of the dry matter and fiber components; CaMg(OH)2 increased the ruminal concentration of butyrate and the abundance of butyrate-producing bacteria. In summary, we conclude that using CaMg(OH)2 can improve ruminal fermentation regardless of buffer use, which indicates that we can take advantage of the mineral formulation in the diet to modulate the ruminal microbiota composition.

pime: A package for discovery of novel differences among microbial communities.

The data used for profiling microbial communities is usually sparse with some microbes having high abundance in a few samples and being nearly absent in others. However, current bioinformatics tools able to deal with this sparsity are lacking. pime (Prevalence Interval for Microbiome Evaluation) was designed to remove those taxa that may be high in relative abundance in just a few samples but have a low prevalence overall. The reliability and robustness of pime were compared against existing methods and tested using 16S rRNA independent data sets. pime filters microbial taxa not shared in a per treatment prevalence interval started at 5% prevalence with increasing increments of 5% at each filtering step. For each prevalence interval, hundreds of decision trees were calculated to predict the likelihood of detecting differences in treatments. The best prevalence-filtered data set was user-selected by choosing the prevalence interval that kept a large portion of the 16S rRNA sequences in the data set while also showing the lowest error rate. To obtain the likelihood of introducing type I error while building prevalence-filtered data sets, an error detection step based was also included. A pime reanalysis of published data sets uncovered other expected microbial associations than previously reported, which may be masked when only relative abundance was considered.

Data analysis for 16S microbial profiling from different benchtop sequencing platforms.

Progress in microbial ecology is confounded by problems when evaluating results from different sequencing methodologies. Contrary to existing expectations, here we demonstrate that the same biological conclusion is reached using different NGS technologies when stringent sequence quality filtering and accurate clustering algorithms are applied.