CRISPR-Cas9-Cytidine deaminase fusion enzymes—termed “base editors”—allow targeted editing of genomic deoxycytidine to deoxythymidine (C:G→T:A) without the need for double-stranded break induction. Base editors represent a paradigm shift in gene editing technology due to their unprecedented efficiency to mediate targeted, single-base conversion. However, current analysis of base editing outcomes rely on methods that are either imprecise or expensive and time-consuming. To overcome these limitations, we developed a simple, cost-effective, and accurate program to measure base editing efficiency from fluorescence-based Sanger sequencing, termed “EditR.” We provide EditR as a free online tool or downloadable desktop application requiring a single Sanger sequencing file and guide RNA sequence. EditR is more accurate than enzymatic assays, and provides added insight to the position, type, and efficiency of base editing. Furthermore, EditR is likely amenable to quantify base editing from the recently developed adenosine deaminase base editors that act on either DNA (adenosine deaminase base editors [ABEs]) or RNA (REPAIRs) (catalyzes A:T→G:C). Collectively, we demonstrate that EditR is a robust, inexpensive tool that will facilitate the broad application of base editing technology, thereby fostering further innovation in this burgeoning field.

Human milk provides essential nutrients for infant nutrition. A large proportion of human milk is composed of human milk oligosaccharides (HMOs), which are resistant to digestion by the infant. Instead, HMOs act as a bioactive and prebiotic enriching HMO-utilizing bacteria and cause systematic changes in the host. Several species of Bifidobacterium have been shown to utilize HMOs by conserved, as well as species-specific pathways, but less work has been done to study variation within species or sub-species. B. longum subsp. infantis is a prevalent species in the breast-fed infant gut and the molecular mechanisms of HMO utilization for the type strain B. longum subsp. infantis ATCC 15697 (type strain) have been well characterized. We used growth, transcriptomic, and metabolite analysis to characterize key differences in the utilization of 2′FL, 3FL and DFL (FLs) between B. longum subsp. infantis Bi-26 (Bi-26) and the type strain. Bi-26 grows faster, produces unique metabolites, and has a distinct global gene transcription response to FLs compared to the type strain. Taken together the findings demonstrate major strain specific adaptations in Bi-26 to efficient utilization of FLs.

Precision medicine requires the translation of basic biological understanding to medical insights, mainly applied to characterization of each unique patient. In many clinical settings, this requires tools that can be broadly used to identify pathology and risks. Patients often present to the intensive care unit with broad phenotypes, including multiple organ dysfunction syndrome (MODS) resulting from infection, trauma, or other disease processes. Etiology and outcomes are unique to individuals, making it difficult to cohort patients with MODS, but presenting a prime target for testing/developing tools for precision medicine. Using multitime point whole blood (cellular/acellular) total transcriptomics in 27 patients, we highlight the promise of simultaneously mapping viral/bacterial load, cell composition, tissue damage biomarkers, balance between syndromic biology versus environmental response, and unique biological insights in each patient using a single platform measurement. Integration of a transcriptome workflow yielded unexpected insights into the complex interplay between host genetics and viral/bacterial specific mechanisms, highlighted by a unique case of virally induced genetics (VIG) within one of these 27 patients. The power of RNA-Seq to study unique patient biology while investigating environmental contributions can be a critical tool moving forward for translational sciences applied to precision medicine.

Background: Multiple organ dysfunction syndrome (MODS) occurs in the setting of a variety of pathologies including infection and trauma. Some patients decompensate and require Veno-Arterial extra corporeal membrane oxygenation (ECMO) as a palliating manoeuvre for recovery of cardiopulmonary function. The molecular mechanisms driving progression from MODS to cardiopulmonary collapse remain incompletely understood, and no biomarkers have been defined to identify those MODS patients at highest risk for progression to requiring ECMO support. Methods: Whole blood RNA-seq profiling was performed for 23 MODS patients at three time points during their ICU stay (at diagnosis of MODS, 72 hours after, and 8 days later), as well as four healthy controls undergoing routine sedation. Of the 23 MODS patients, six required ECMO support (ECMO patients). The predictive power of conventional demographic and clinical features was quantified for differentiating the MODS and ECMO patients. We then compared the performance of markers derived from transcriptomic profiling including [1] transcriptomically imputed leukocyte subtype distribution, [2] relevant published gene signatures and [3] a novel differential gene expression signature computed from our data set. The predictive power of our novel gene expression signature was then validated using independently published datasets. Finding: None of the five demographic characteristics and 14 clinical features, including The Paediatric Logistic Organ Dysfunction (PELOD) score, could predict deterioration of MODS to ECMO at baseline. From previously published sepsis signatures, only the signatures positively associated with patient's mortality could differentiate ECMO patients from MODS patients, when applied to our transcriptomic dataset (P-value ranges from 0.01 to 0.04, Student's test). Deconvolution of bulk RNA-Seq samples suggested that lower neutrophil counts were associated with increased risk of progression from MODS to ECMO (P-value = 0.03, logistic regression, OR=2.82 [95% CI 0.63-12.45]). A total of 30 genes were differentially expressed between ECMO and MODS patients at baseline (log2 fold change 1 or-1 with false discovery rate 0.01). These genes are involved in protein maintenance and epigenetic-related processes. Further univariate analysis of these 30 genes suggested a signature of seven DE genes associated with ECMO (OR > 3.0, P-value 0.05, logistic regression). Notably, this contains a set of histone marker genes, including H1F0, HIST2H3C, HIST1H2AI, HIST1H4, HIST1H2BL and HIST1H1B, that were highly expressed in ECMO. A risk score derived from expression of these genes differentiated ECMO and MODS patients in our dataset (AUC = 0.91, 95% CI 0.79-1.00, Pvalue = 7e-04, logistic regression) as well as validation dataset (AUC= 0.73, 95% CI 0.53-0.93, P-value = 2e-02, logistic regression).

Microclimatic conditions change dramatically as forests age and impose strong filters on community assembly during succession. Light availability is the most limiting environmental factor in tropical wet forest succession; by contrast, water availability is predicted to strongly influence tropical dry forest (TDF) successional dynamics. While mechanisms underlying TDF successional trajectories are not well understood, observational studies have demonstrated that TDF communities transition from being dominated by species with conservative traits to species with acquisitive traits, the opposite of tropical wet forest. Determining how functional traits predict TDF tree species’ responses to changing environmental conditions could elucidate mechanisms underlying tree performance during TDF succession. We implemented a 6‐ha restoration experiment on a degraded Vertisol in Costa Rica to determine (1) how TDF tree species with different resource‐use strategies performed along a successional gradient and (2) how ecophysiological functional traits correlated with tree performance in simulated successional stages. We used two management treatments to simulate distinct successional stages including: clearing all remnant vegetation (early‐succession), or interplanting seedlings with no clearing (mid‐succession). We crossed these two management treatments (cleared/interplanted) with two species mixes with different resource‐use strategies (acquisitive/conservative) to examine their interaction. Overall seedling survival after 2 yr was low, 15.1–26.4% in the four resource‐use‐strategy × management‐treatment combinations, and did not differ between the management treatments or resource‐use‐strategy groups. However, seedling growth rates were dramatically higher for all species in the cleared treatment (year 1, 69.1% higher; year 2, 143.3% higher) and defined resource‐use strategies had some capacity to explain seedling performance. Overall, ecophysiological traits were better predictors of species’ growth and survival than resource‐use strategies defined by leaf and stem traits such as specific leaf area. Moreover, ecophysiological traits related to water use had a stronger influence on seedling performance in the cleared, early‐successional treatment, indicating that the influence of microclimatic conditions on tree survival and growth shifts predictably during TDF succession. Our findings suggest that ecophysiological traits should be explicitly considered to understand shifts in TDF functional composition during succession and that using these traits to design species mixes could greatly improve TDF restoration outcomes.