Microbiome composition recovery after liver transplantation correlates with initial liver disease severity and antibiotics treatment.

Liver transplantation (LT) is crucial for end-stage liver disease, but it is linked to infection risks. Pathobionts, microorganisms potentially harmful under specific conditions, can cause complications posttransplant. Monitoring such pathogens in fecal samples can be challenging and therefore remains underexplored post-LT. This study aimed to analyze the gut microbiome before and after LT, tracking pathobionts and correlating clinical data. The study involved 17 liver transplant recipients, 17 healthy relatives (spouses), and 13 donors. Gut samples collected pretranplantation and posttransplantation underwent bacterial and fungal profiling through DNA sequencing. Quantitative polymerase chain reaction was used to assess microbial load. Statistical analyses included alpha and beta diversity measures, differential abundance analysis, and correlation tests between microbiome and clinical parameters. Microbiome analysis revealed dynamic changes in diversity posttransplant. Notably, high-severity patients showed persistent and greater dysbiosis during the first months post-LT compared with low-severity patients, partly due to an antibiotic treatment pre-LT. The analysis identified a higher proportion of pathogens such as Escherichia coli/Shigella flexneri in high-severity cases posttransplant. Furthermore, butyrate producers including Roseburia intestinalis, Anaerostipes hadrus, and Eubacterium coprostanoligenes were positively correlated with levels of albumin. This study offers valuable insights into post-LT microbiome changes, shedding light on the need for tailored prophylactic treatment post-LT.

Mechanism of aroma enhancement methods in accelerating Congou black tea acidification subjected to room temperature storage.

Acidification of aroma-enhanced black tea during storage was studied. UPLC-Q-TOF/MS (Ultra Performance Liquid Chromatography and Quadrupole-Time of Flight Mass Spectrometer) and HPLC (High-Performance Liquid Chromatography) analysis of non-volatile substances and organic acids revealed a decrease of soluble sugars and amino acids in aroma-enhanced black tea, while an increase in organic acids such as oxalic acid, malic acid and quinic acid. Further in vitro experiments indicated that the acidification of aroma-enhanced tea during storage can be attributed to decomposition of sugars and amino acids by heating, oxidation of aromatic aldehydes. Meanwhile, the amino acids, catechins, soluble sugars and flavonoids that constitute the taste of black tea are further reduced, changing the taste composition of tea infusion and further increasing its acidity. This study revealed the reasons for black tea acidification during aroma enhancement and storage and provided a theoretical basis for improving black tea quality.

Shotgun metagenomics reveals interkingdom association between intestinal bacteria and fungi involving competition for nutrients.

BACKGROUND: The accuracy of internal-transcribed-spacer (ITS) and shotgun metagenomics has not been robustly evaluated, and the effect of diet on the composition and function of the bacterial and fungal gut microbiome in a longitudinal setting has been poorly investigated. Here we compared two approaches to study the fungal community (ITS and shotgun metagenomics), proposed an enrichment protocol to perform a reliable mycobiome analysis using a comprehensive in-house fungal database, and correlated dietary data with both bacterial and fungal communities. RESULTS: We found that shotgun DNA sequencing after a new enrichment protocol combined with the most comprehensive and novel fungal databases provided a cost-effective approach to perform gut mycobiome profiling at the species level and to integrate bacterial and fungal community analyses in fecal samples. The mycobiome was significantly more variable than the bacterial community at the compositional and functional levels. Notably, we showed that microbial diversity, composition, and functions were associated with habitual diet composition instead of driven by global dietary changes. Our study indicates a potential competitive inter-kingdom interaction between bacteria and fungi for food foraging. CONCLUSION: Together, our present work proposes an efficient workflow to study the human gut microbiome integrating robustly fungal, bacterial, and dietary data. These findings will further advance our knowledge of the interaction between gut bacteria and fungi and pave the way for future investigations in human mycobiome. Video Abstract.

Unveiling Candida albicans intestinal carriage in healthy volunteers: the role of micro- and mycobiota, diet, host genetics and immune response.

Candida albicans is a commensal yeast present in the gut of most healthy individuals but with highly variable concentrations. However, little is known about the host factors that influence colonization densities. We investigated how microbiota, host lifestyle factors, and genetics could shape C. albicans intestinal carriage in 695 healthy individuals from the Milieu Intérieur cohort. C. albicans intestinal carriage was detected in 82.9% of the subjects using quantitative PCR. Using linear mixed models and multiway-ANOVA, we explored C. albicans intestinal levels with regard to gut microbiota composition and lifestyle factors including diet. By analyzing shotgun metagenomics data and C. albicans qPCR data, we showed that Intestinimonas butyriciproducens was the only gut microbiota species whose relative abundance was negatively correlated with C. albicans concentration. Diet is also linked to C. albicans growth, with eating between meals and a low-sodium diet being associated with higher C. albicans levels. Furthermore, by Genome-Wide Association Study, we identified 26 single nucleotide polymorphisms suggestively associated with C. albicans colonization. In addition, we found that the intestinal levels of C. albicans might influence the host immune response, specifically in response to fungal challenge. We analyzed the transcriptional levels of 546 immune genes and the concentration of 13 cytokines after whole blood stimulation with C. albicans cells and showed positive associations between the extent of C. albicans intestinal levels and NLRP3 expression, as well as secreted IL-2 and CXCL5 concentrations. Taken together, these findings open the way for potential new interventional strategies to curb C. albicans intestinal overgrowth.

Dysbiosis: An Indicator of COVID-19 Severity in Critically Ill Patients.

Here, we examined the dynamics of the gut and respiratory microbiomes in severe COVID-19 patients in need of mechanical ventilation in the intensive care unit (ICU). We recruited 85 critically ill patients (53 with COVID-19 and 32 without COVID-19) and 17 healthy controls (HCs) and monitored them for up to 4 weeks. We analyzed the bacterial and fungal taxonomic profiles and loads of 232 gut and respiratory samples and we measured the blood levels of Interleukin 6, IgG, and IgM in COVID-19 patients. Upon ICU admission, the bacterial composition and load in the gut and respiratory samples were altered in critically ill patients compared with HCs. During their ICU stay, the patients experienced increased bacterial and fungal loads, drastic decreased bacterial richness, and progressive changes in bacterial and fungal taxonomic profiles. In the gut samples, six bacterial taxa could discriminate ICU-COV(+) from ICU-COV(-) cases upon ICU admission and the bacterial taxa were associated according to age, PaO2/FiO2, and CRP levels. In the respiratory samples of the ICU-COV(+) patients, bacterial signatures including Pseudomonas and Streptococcus were found to be correlated with the length of ICU stay. Our findings demonstrated that the gut and respiratory microbiome dysbiosis and bacterial signatures associated with critical illness emerged as biomarkers of COVID-19 severity and could be a potential predictor of ICU length of stay. We propose using a high-throughput sequencing approach as an alternative to traditional isolation techniques to monitor ICU patient infection.

Intercontinental Gut Microbiome Variances in IBD.

The development of biomarkers for inflammatory bowel disease (IBD) diagnosis would be relevant in a generalized context. However, intercontinental investigation on these microbial biomarkers remains scarce. We examined taxonomic microbiome variations in IBD using published DNA shotgun metagenomic data. For this purpose, we used sequenced data from our previous Spanish Crohn's disease (CD) and ulcerative colitis (UC) cohort, downloaded sequence data from a Chinese CD cohort, and downloaded taxonomic and functional profiling tables from a USA CD and UC cohort. At the global level, geographical location and disease phenotype were the main explanatory covariates of microbiome variations. In healthy controls (HC) and UC, geography turned out to be the most important factor, while disease intestinal location was the most important one in CD. Disease severity correlated with lower alpha-diversity in UC but not in CD. Across geography, alpha-diversity was significantly different independently of health status, except for CD. Despite recruitment from different countries and with different disease severity scores, CD patients may harbor a very similar microbial taxonomic profile. Our study pointed out that geographic location, disease activity status, and other environmental factors are important contributing factors in microbiota changes in IBD. We therefore strongly recommend taking these factors into consideration for future IBD studies to obtain globally valid and reproducible biomarkers.

Cervical pessary and cerclage placement for preterm birth prevention and cervicovaginal microbiome changes.

INTRODUCTION: Our objective was to compare the vaginal microbiome in low-risk and high-risk pregnant women and to explore a potential association between vaginal microbiome and preterm birth. MATERIAL AND METHODS: A pilot, consecutive, longitudinal, multicenter study was conducted in pregnant women at 18-22 weeks of gestation. Participants were assigned to one of three groups: control (normal cervix), pessary (cervical length ≤25 mm) and cerclage (cervical length ≤25 mm or history of preterm birth). Analysis and comparison of vaginal microbiota as a primary outcome was performed at inclusion and at 30 weeks of gestation, along with a follow-up of pregnancy and perinatal outcomes. We assessed the vaginal microbiome of pregnant women presenting a short cervix with that of pregnant women having a normal cervix, and compared the vaginal microbiome of women with a short cervix before and after placement of a cervical pessary or a cervical cerclage. RESULTS: The microbiome of our control cohort was dominated by Lactobacillus crispatus and inners. Five community state types were identified and microbiome diversity did not change significantly over 10 weeks in controls. On the other hand, a short cervix was associated with a lower microbial load and higher microbial richness, and was not correlated with Lactobacillus relative abundance. After intervention, the cerclage group (n = 19) had a significant increase in microbial richness and a shift towards community state types driven by various bacterial species, including Lactobacillus mulieris, unidentified Bifidobacterium or Enterococcus. These changes were not significantly observed in the pessary (n = 26) and control (n = 35) groups. The cerclage group had more threatened preterm labor episodes and poorer outcomes than the control and pessary groups. CONCLUSIONS: These findings indicate that a short cervix is associated with an altered vaginal microbiome community structure. The use of a cerclage for preterm birth prevention, as compared with a pessary, was associated with a microbial community harboring a relatively low abundance of Lactobacillus, with more threatened preterm labor episodes, and with poorer clinical outcomes.

FunOMIC: Pipeline with built-in fungal taxonomic and functional databases for human mycobiome profiling.

While analysis of the bacterial microbiome has become routine, that of the fungal microbiome is still hampered by the lack of robust databases and bioinformatic pipelines. Here, we present FunOMIC, a pipeline with built-in taxonomic (1.6 million marker genes) and functional (3.4 million non-redundant fungal proteins) databases for the identification of fungi. Applied to more than 2,600 human metagenomic samples, the tool revealed fungal species associated with geography, body sites, and diseases. Correlation network analysis provided new insights into inter-kingdom interactions. With this pipeline and two of the most comprehensive fungal databases, we foresee a fast-growing resource for mycobiome studies.

A systematic assessment of city-level climate change mitigation and air quality improvement in China.

China is facing dual challenges of air pollution and climate change. By using city-level data, we comprehensively assessed air quality and CO2 emission changes from 2015 to 2019 for 335 Chinese cities. We selected important regions for air pollution control and categorized all cities into different classes according to their development levels. Our novel approach revealed new insights on different patterns of changes of PM2.5, O3, and CO2 by region and city class. We found that PM2.5 concentrations decreased remarkably due to mandatory city-level reduction targets, especially in the Beijing-Tianjin-Hebei (-27%) region. Nonetheless, O3 concentrations and CO2 emissions increased in 91% and 69% of Chinese cities, respectively. Observed CO2 emission reductions in more developed cities were mainly due to prominent energy intensity reduction and energy structure improvement. Our study indicates a lack of synergy in air pollution control and CO2 mitigation under current policies in China. To address both challenges holistically, we suggest setting mandatory city-level CO2 emission reduction targets and reinforcing clean energy and energy efficiency measures.

Human gut metatranscriptome changes induced by a fermented milk product are associated with improved tolerance to a flatulogenic diet.

Healthy plant-based diets rich in fermentable residues may induce gas-related symptoms, possibly mediated by the gut microbiota. We previously showed that consumption of a fermented milk product (FMP) containing Bifidobacterium animalis subsp. lactis CNCM I-2494 and lactic acid bacteria improved gastrointestinal (GI) comfort in response to a flatulogenic dietary challenge in healthy individuals. To study the effects of the FMP on gut microbiota activity from those participants, we conducted a metatranscriptomic analysis of fecal samples (n = 262), which were collected during the ingestion of a habitual diet and two series of a 3-day high-residue challenge diet, before and following 28-days of FMP consumption. Most of the FMP species were detected or found enriched upon consumption of the product. FMP mitigated the effect of a flatulogenic diet on gas-related symptoms in several ways. First, FMP consumption was associated with the depletion of gas-producing bacteria and increased hydrogen to methane conversion. It also led to the upregulation of activities such as replication and downregulation of functions related to motility and chemotaxis. Furthermore, upon FMP intake, metabolic activities such as carbohydrate metabolism, attributed to B. animalis and S. thermophilus, were enriched; these activities were coincidentally found to be negatively associated with several GI symptoms. Finally, a more connected microbial ecosystem or mutualistic relationship among microbes was found in responders to the FMP intervention. Taken together, these findings suggest that consumption of the FMP improved the tolerance of a flatulogenic diet through active interactions with the resident gut microbiota.

Subpopulation Particle Swarm Optimization with a Hybrid Mutation Strategy.

With the large-scale optimization problems in the real world becoming more and more complex, they also require different optimization algorithms to keep pace with the times. Particle swarm optimization algorithm is a good tool that has been proved to deal with various optimization problems. Conventional particle swarm optimization algorithms learn from two particles, namely, the best position of the current particle and the best position of all particles. This particle swarm optimization algorithm is simple to implement, simple, and easy to understand, but it has a fatal defect. It is hard to find the global optimal solution quickly and accurately. In order to deal with these defects of standard particle swarm optimization, this paper proposes a particle swarm optimization algorithm (SHMPSO) based on the hybrid strategy of seed swarm optimization (using codes available from https://gitee.com/mr-xie123234/code/tree/master/). In SHMPSO, a subpopulation coevolution particle swarm optimization algorithm is adopted. In SHMPSO, an elastic candidate-based strategy is used to find a candidate and realize information sharing and coevolution among populations. The mean dimension learning strategy can be used to make the population converge faster and improve the solution accuracy of SHMPSO. Twenty-one benchmark functions and six industries-recognized particle swarm optimization variants are used to verify the advantages of SHMPSO. The experimental results show that SHMPSO has good convergence speed and good robustness and can obtain high-precision solutions.

Monitoring the damage of armyworm as a pest in summer corn by unmanned aerial vehicle imaging.

BACKGROUND: The timely, rapid, and accurate near real-time observations are urgent to monitor the damage of corn armyworm, because the rapid expansion of armyworm would lead to severe yield losses. Therefore, the potential of machine learning algorithms for identifying the armyworm infected areas automatically and accurately by multispectral unmanned aerial vehicle (UAV) dataset is explored in this study. The study area is in Beicuizhuang Village, Langfang City, Hebei Province, which is the main corn-producing area in the North China Plain. RESULTS: Firstly, we identified the optimal combination of image features by Gini-importance and the comparation of four kinds of machine learning methods including Random Forest (RF), Multilayer Perceptron (MLP), Naive Bayesian (NB) and Support Vector Machine (SVM) was done. And RF was proved to be the most potential with the highest Kappa and OA of 0.9709 and 0.9850, respectively. Secondly, the armyworm infected areas and healthy corn areas were predicted by an optimized RF model in the UAV dataset, and the armyworm incidence levels were classified subsequently. Thirdly, the relationship between the spectral characteristics of different bands and pest incidence levels within the Sentinel-2 and UAV images were analyzed, and the B3 in UAV images and the B6 in Sentinel-2 image were less sensitive for armyworm incidence levels. Therefore, the Sentinel-2 image was used to monitor armyworm in two towns. CONCLUSIONS: The optimized dataset and RF model are effective and reliable, which can be used for identifying the corn damage by armyworm using UAV images accurately and automatically in field-scale. © 2022 Society of Chemical Industry.

Integrating Dietary Data into Microbiome Studies: A Step Forward for Nutri-Metaomics.

Diet is recognised as the main driver of changes in gut microbiota. However, linking habitual dietary intake to microbiome composition and activity remains a challenge, leaving most microbiome studies with little or no dietary information. To fill this knowledge gap, we conducted two consecutive studies (n = 84: a first pilot study (n = 40) to build a web-based, semi-quantitative simplified FFQ (sFFQ) based on three 24-h dietary recalls (24HRs); a second study (n = 44) served to validate the newly developed sFFQ using three 24HRs as reference method and to relate gut microbiome profiling (16S rRNA gene) with the extracted dietary and lifestyle data. Relative validation analysis provided acceptable classification and agreement for 13 out of 24 (54%) food groups and 20 out of 29 nutrients (69%) based on intraclass correlation coefficient, cross-classification, Spearman's correlation, Wilcoxon test, and Bland-Altman. Microbiome analysis showed that higher diversity was positively associated with age, vaginal birth, and intake of fruit. In contrast, microbial diversity was negatively associated with BMI, processed meats, ready-to-eat meals, sodium, and saturated fat. Our analysis also revealed a correlation between food groups or nutrients and microbial composition. Overall, we provide the first dietary assessment tool to be validated and correlated with microbiome data for population studies.

The impact of the Fungus-Host-Microbiota interplay upon Candida albicans infections: current knowledge and new perspectives.

Candida albicans is a major fungal pathogen of humans. It exists as a commensal in the oral cavity, gut or genital tract of most individuals, constrained by the local microbiota, epithelial barriers and immune defences. Their perturbation can lead to fungal outgrowth and the development of mucosal infections such as oropharyngeal or vulvovaginal candidiasis, and patients with compromised immunity are susceptible to life-threatening systemic infections. The importance of the interplay between fungus, host and microbiota in driving the transition from C. albicans commensalism to pathogenicity is widely appreciated. However, the complexity of these interactions, and the significant impact of fungal, host and microbiota variability upon disease severity and outcome, are less well understood. Therefore, we summarise the features of the fungus that promote infection, and how genetic variation between clinical isolates influences pathogenicity. We discuss antifungal immunity, how this differs between mucosae, and how individual variation influences a person's susceptibility to infection. Also, we describe factors that influence the composition of gut, oral and vaginal microbiotas, and how these affect fungal colonisation and antifungal immunity. We argue that a detailed understanding of these variables, which underlie fungal-host-microbiota interactions, will present opportunities for directed antifungal therapies that benefit vulnerable patients.

Early Postoperative Endoscopic Recurrence in Crohn's Disease Is Characterised by Distinct Microbiota Recolonisation.

BACKGROUND AND AIMS: Intestinal microbiota dysbiosis is implicated in Crohn's disease [CD] and may play an important role in triggering postoperative disease recurrence [POR]. We prospectively studied faecal and mucosal microbial recolonisation following ileocaecal resection to identify the predictive value of recurrence-related microbiota. METHODS: Mucosal and/or faecal samples from 121 CD patients undergoing ileocaecal resection were collected at predefined time points before and after surgery. Ileal biopsies were collected from 39 healthy controls. POR was defined by a Rutgeerts score ≥i2b. The microbiota was evaluated by 16S rRNA sequencing. Prediction analysis was performed using C5.0 and Random Forest algorithms. RESULTS: The mucosa-associated microbiota in CD patients was characterised by a depletion of butyrate-producing species (false discovery rate [FDR] <0.01) and enrichment of Proteobacteria [FDR = 0.009] and Akkermansia spp. [FDR = 0.02]. Following resection, a mucosal enrichment of Lachnospiraceae [FDR <0.001] was seen in all patients but in POR patients, also Fusobacteriaceae [FDR <0.001] increased compared with baseline. Patients without POR showed a decrease of Streptococcaceae [FDR = 0.003] and Actinomycineae [FDR = 0.06]. The mucosa-associated microbiota profile had good discriminative power to predict POR, and was superior to clinical risk factors. At Month 6, patients experiencing POR had a higher abundance of taxa belonging to Negativicutes [FDR = 0.04] and Fusobacteria [FDR = 0.04] compared with patients without POR. CONCLUSIONS: Microbiota recolonisation after ileocaecal resection is different between recurrence and non-recurrence patients, with Fusobacteria as the most prominent player driving early POR. These bacteria involved in the early recolonisation and POR represent a promising therapeutic strategy in the prevention of disease recurrence.

Hollow PtCu octahedral nanoalloys: Efficient bifunctional electrocatalysts towards oxygen reduction reaction and methanol oxidation reaction by regulating near-surface composition.

In response to the scarcity of precious metals, the development of precious-metal-saving electrocatalysts exhibiting high mass activity (MA) and durability towards oxygen reduction reaction (ORR) and methanol oxidation reaction (MOR) for both proton-exchange membrane fuel cells (PEMFCs) and direct methanol fuel cells (DMFCs) has aroused increasing attention. In this study, octahedral Cu-rich PtCu alloy is seeded to fabricate near-surface composition-tunable PtCu hollow octahedral nanoparticles (HONs) with the wall thickness of ~2.1 nm. Due to both the alloying effects of near surface and the special hollow octahedral structure, the PtCu/C HONs exhibit significantly higher MA and durability than commercial Pt/C towards both ORR in alkaline medium and MOR in sulfuric acid electrolyte. The ORR MA of Pt44.1Cu55.9/C HONs are up to 2.60 A mgPt-1 that is 18.5-fold enhancement compared with that of Pt/C. Besides, after 10,000 voltage cycles, the MA of Pt44.1Cu55.9/C HONs remains to be 1.61 A mgPt-1, a datum 53.7 times that of Pt/C. The in situ CO polarization curves exhibit that the Pt44.1Cu55.9 HONs/C own high resistance to CO poisoning. For MOR in sulfuric acid electrolyte, the optimum SA/MA of PtCu/C HONs is 5.33 mA cm-2/1.94 A mgPt-1, which is 10.25/5.87 times higher than that of Pt/C. This study provides effective bifunctional cathode and anode electrocatalysts for both PEMFCs and DMFCs.

Trimetallic palladium-copper-cobalt alloy wavy nanowires improve ethanol electrooxidation in alkaline medium.

Recently, engineering high performance Pd-based nanocatalysts for alkaline ethanol fuel cells has attracted wide attention. Here, we report a one-pot synthesis of low-palladium ternary palladium-copper-cobalt (PdCuCo) alloy nanowires (NWs) with a diameter of ∼4.0 nm to improve the mass activity (MA) of ethanol electrooxidation in alkaline medium. The MA (7.45 A mg-1) of the Pd31Cu61Co8 NWs is 8.5-fold and 12.4-fold that of commercial Pd black and Pd/C, respectively. The reaction mechanism of the EOR and the reasons for the activity enhancement on Pd31Cu61Co8 NWs are elucidated based on the results of in situ Fourier transform infrared spectroscopy and structure characterization. Besides the electronic effect and surface defect sites, the coexistence of surface Cu and Co that have high capacities to activate water to produce reactive oxygen species is another key factor. This study shows an example of how to design low-palladium ternary PdCuCo NWs as improved anode electrocatalysts for alkaline direct ethanol fuel cells with high mass activity.

Polyhedron-Assembled Ternary PtCuCo Nanochains: Integrated Functions Enhance the Electrocatalytic Performance of Methanol Oxidation at Elevated Temperature.

Recently, the preparation of a high-performance one-dimensional alloy nanostructure for fuel cells has been given increasing attention due to its smart-structure merits and electronic effect triggered by alloying different kinds of metals at the nanoscale. In this study, unique ternary PtCuCo nanochains assembled with small polyhedra are first achieved and used as high-performance anode electrocatalysts toward methanol oxidation at elevated temperature (60 °C) that is closer to the operating temperature of direct methanol fuel cells than room temperature. The specific activity/mass activity of Pt45Cu35Co20 one-dimensional nanochains can reach up to 18.24 mA cm-2/4.19 A mg-1Pt that is 9.25/10.47 times that of commercial Pt black in sulfuric acid medium. After a 3600 s durability test, the remaining current density of Pt45Cu35Co20 one-dimensional nanochains is 73.3 times that of commercial Pt black. The structure characterizations show that the high density of surface active sites, d-band center of the Pt downshift, moderate strain effect, and synergetic effect are jointly responsible for the enhanced electrocatalytic performance of one-dimensional ternary PtCuCo nanochains.

Correlation Analyses Reveal a Limited Role of Transcription in Genome-Wide Differential MicroRNA Expression in Mammals.

Transcription initiates the cascade of gene expression and is often assumed to play a predominant role in determining how much gene products are ultimately expressed. The relationship between mRNA levels and protein levels has been studied extensively to reveal the degrees of transcriptional and post-transcriptional regulation of protein expression. The extent to which transcription globally controls the differential expression of non-coding RNAs, however, is poorly defined. MicroRNAs (miRNAs) are a class of small, non-coding RNAs whose biogenesis involves transcription followed by extensive processing. Here, using hundreds of datasets produced from the ENCODE (Encyclopedia of DNA Elements) project we calculated the correlations between transcriptional activity and mature miRNA expression in diverse human cells, human tissues, and mouse tissues. While correlations vary among samples, most correlation coefficients are small. Interestingly, excluding miRNAs that were discovered later or weighting miRNA expression improves the correlations. Our results suggest that transcription contributes only modestly to differential miRNA expression at the genome-wide scale in mammals.

Examining Community Stability in the Face of Mass Extinction in Communities of Digital Organisms.

Digital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent platform for addressing topics in long-term evolution and paleobiology, such as mass extinction and recovery, with experimental evolutionary approaches. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths, along with unperturbed control experiments. We examined how stability in the digital communities was affected from the perspectives of division of labor, relative shift in rank abundance, and genealogical connectedness of the community's component ecotypes. Mass extinction that was due to a Strong Press treatment was most effective in producing reshaped communities that differed from the pre-treatment ones in all of the measured perspectives; weaker versions of the treatments did not generally produce significant departures from a Control treatment; and results for the Strong Pulse treatment generally fell between those extremes. The Strong Pulse treatment differed from others in that it produced a slight but detectable shift towards more generalized communities. Compared to Press treatments, Pulse treatments also showed a greater contribution from re-evolved ecological doppelgangers rather than new ecotypes. However, relatively few Control communities showed stability in any of these metrics over the whole course of the experiment, and most did not represent stable states (by some measure of stability) that were disrupted by the extinction treatments. Our results have interesting, broad qualitative parallels with findings from the paleontological record, and show the potential of digital evolution studies to illuminate many aspects of mass extinction and recovery by addressing them in a truly experimental manner.