The fecal microbiota of Holstein cows is heritable and genetically correlated to dairy performances.

The fecal microbiota of ruminants constitutes a diversified community that has been phenotypically associated with a variety of host phenotypes, such as production and health. To gain a better understanding of the complex and interconnected factors that drive the fecal bacterial community, we have aimed to estimate the genetic parameters of the diversity and composition of the fecal microbiota, including heritabilities, genetic correlations among taxa, and genetic correlations between fecal microbiota features and host phenotypes. To achieve this, we analyzed a large population of 1,875 Holstein cows originating from 144 French commercial herds and routinely recorded for production, somatic cell score, and fertility traits. Fecal samples were collected from the animals and subjected to 16S rRNA gene sequencing, with reads classified into Amplicon Sequence Variants (ASVs). The estimated α- and ß-diversity indices (i.e., Observed Richness, Shannon index, Bray-Curtis and Jaccard dissimilarity matrices) and the abundances of ASVs, genera, families and phyla, normalized by centered-log ratio (CLR), were considered as phenotypes. Genetic parameters were calculated using either univariate or bivariate animal models. Heritabilities estimates, ranging from 0.08 to 0.31 for taxa abundances and ß-diversity indices, highlight the influence of the host genetics on the composition of the fecal microbiota. Furthermore, genetic correlations estimated within the microbial community and between microbiota features and host traits reveal the complex networks linking all components of the fecal microbiota together and to their host, thus strengthening the holobiont concept. By estimating the heritabilities of microbiota-associated phenotypes, our study quantifies the impact of the host genetics on the fecal microbiota composition. In addition, genetic correlations between taxonomic groups and between taxa abundances and host performance suggest potential applications for selective breeding to improve host traits or promote a healthier microbiota.

Digestion of Lipid-Based Formulations Not Only Mediates Changes to Absorption of Poorly Soluble Drugs Due to Differences in Solubilization But Also Reflects Changes to Thermodynamic Activity and Permeability.

The aim of this study was to evaluate the effect of lipid digestion on the permeability and absorption of orally administered saquinavir (SQV), a biopharmaceutics classification system (BCS) class IV drug, in different lipid-based formulations. Three LBFs were prepared: a mixed short- and medium-chain lipid-based formulation (SMCF), a medium-chain lipid-based formulation (MCF), and a long-chain lipid-based formulation (LCF). SQV was loaded into these LBFs at 26.7 mg/g. To evaluate the pharmacokinetics of SQV in vivo, drug-loaded formulations were predispersed in purified water at 3% w/w and orally administered to rats. A low dose (0.8 mg/rat) was employed to limit confounding effects on drug solubilization, and consistent with this design, presolubilization of SQV in the LBFs did not increase in vivo exposure compared to a control suspension formulation. The areas under the plasma concentration-time curve were, however, significantly lower after administration of SQV as MCF and LCF compared to SMCF. To evaluate the key mechanisms underpinning absorption, each LBF containing SQV was digested, and the flux of SQV from the digests across a dialysis membrane was evaluated in in vitro permeation experiments. This study revealed that the absorption profiles were driven by the free concentration of SQV and that this varied due to differences in SQV solubilization in the digestion products generated by LBF digestion. The apparent first-order permeation rate constants of SQV (kapp,total) were estimated by dividing the flux of SQV in the dialysis membrane experiments by the concentration of total SQV on the donor side. kapp,total values strongly correlated with in vivo AUC. The data provide one of the first studies of the effect of digestion products on the free concentration of a drug in the GI fluid and oral absorption. This simple permeation model may be a useful tool for the evaluation of the impact of lipid digestion on apparent drug permeability from lipid-based formulations. These effects should be assessed alongside, and in addition to, the more well-known effects of lipids on enhancing intestinal solubilization of poorly water-soluble drugs.

Transcription from a gene desert in a melanoma porcine model.

The genetic mechanisms underlying cutaneous melanoma onset and progression need to be further understood to improve patients' care. Several studies have focused on the genetic determinism of melanoma development in the MeLiM pig, a biomedical model of cutaneous melanoma. The objective of this study was to better describe the influence of a particular genomic region on melanoma progression in the MeliM model. Indeed, a large region of the Sus scrofa chromosome 1 has been identified by linkage and association analyses, but the causal mechanisms have remained elusive. To deepen the analysis of this candidate region, a dedicated SNP panel was used to fine map the locus, downsizing the interval to less than 2 Mb, in a genomic region located within a large gene desert. Transcription from this locus was addressed using a tiling array strategy and further validated by RT-PCR in a large panel of tissues. Overall, the gene desert showed an extensive transcriptional landscape, notably dominated by repeated element transcription in tumor and fetal tissues. The transcription of LINE-1 and PERVs has been confirmed in skin and tumor samples from MeLiM pigs. In conclusion, although this study still does not identify a candidate mutation for melanoma occurrence or progression, it highlights a potential role of repeated element transcriptional activity in the MeLiM model.

Polymeric Precipitation Inhibitors Promote Fenofibrate Supersaturation and Enhance Drug Absorption from a Type IV Lipid-Based Formulation.

The ability of lipid-based formulations (LBFs) to increase the solubilization, and prolong the supersaturation, of poorly water-soluble drugs (PWSDs) in the gastrointestinal (GI) fluids has generated significant interest in the past decade. One mechanism to enhance the utility of LBFs is to prolong supersaturation via the addition of polymers that inhibit drug precipitation (polymeric precipitation inhibitors or PPIs) to the formulation. In this work, we have evaluated the performance of a range of PPIs and have identified PPIs that are sufficiently soluble in LBF to allow the construction of single phase formulations. An in vitro model was first employed to assess drug (fenofibrate) solubilization and supersaturation on LBF dispersion and digestion. An in vitro-in situ model was subsequently employed to simultaneously evaluate the impact of PPI enhanced drug supersaturation on drug absorption in rats. The stabilizing effect of the polymers was polymer specific and most pronounced at higher drug loads. Polymers that were soluble in LBF allowed simple processing as single phase formulations, while formulations containing more hydrophilic polymers required polymer suspension in the formulation. The lipid-soluble polymers Eudragit (EU) RL100 and poly(propylene glycol) bis(2-aminopropyl ether) (PPGAE) and the water-soluble polymer hydroxypropylmethyl cellulose (HPMC) E4M were identified as the most effective PPIs in delaying fenofibrate precipitation in vitro. An in vitro model of lipid digestion was subsequently coupled directly to an in situ single pass intestinal perfusion assay to evaluate the influence of PPIs on fenofibrate absorption from LBFs in vivo. This coupled model allowed for real-time evaluation of the impact of supersaturation stabilization on absorptive drug flux and provided better discrimination between the different PPIs and formulations. In the presence of the in situ absorption sink, increased fenofibrate supersaturation resulted in increased drug exposure, and a good correlation was found between the degree of in vitro supersaturation and in vivo drug exposure. An improved in vitro-in vivo correlation was apparent when comparing the same formulation under different supersaturation conditions. These observations directly exemplify the potential utility of PPIs in promoting drug absorption from LBF, via stabilization of supersaturation, and further confirm that relatively brief periods of supersaturation may be sufficient to promote drug absorption, at least for highly permeable drugs such as fenofibrate.

Deciphering the genetic regulation of peripheral blood transcriptome in pigs through expression genome-wide association study and allele-specific expression analysis.

BACKGROUND: Efforts to improve sustainability in livestock production systems have focused on two objectives: investigating the genetic control of immune function as it pertains to robustness and disease resistance, and finding predictive markers for use in breeding programs. In this context, the peripheral blood transcriptome represents an important source of biological information about an individual's health and immunological status, and has been proposed for use as an intermediate phenotype to measure immune capacity. The objective of this work was to study the genetic architecture of variation in gene expression in the blood of healthy young pigs using two approaches: an expression genome-wide association study (eGWAS) and allele-specific expression (ASE) analysis. RESULTS: The blood transcriptomes of 60-day-old Large White pigs were analyzed by expression microarrays for eGWAS (242 animals) and by RNA-Seq for ASE analysis (38 animals). Using eGWAS, the expression levels of 1901 genes were found to be associated with expression quantitative trait loci (eQTLs). We recovered 2839 local and 1752 distant associations (Single Nucleotide Polymorphism or SNP located less or more than 1 Mb from expression probe, respectively). ASE analyses confirmed the extensive cis-regulation of gene transcription in blood, and revealed allelic imbalance in 2286 SNPs, which affected 763 genes. eQTLs and ASE-genes were widely distributed on all chromosomes. By analyzing mutually overlapping eGWAS results, we were able to describe putative regulatory networks, which were further refined using ASE data. At the functional level, genes with genetically controlled expression that were detected by eGWAS and/or ASE analyses were significantly enriched in biological processes related to RNA processing and immune function. Indeed, numerous distant and local regulatory relationships were detected within the major histocompatibility complex region on chromosome 7, revealing ASE for most class I and II genes. CONCLUSIONS: This study represents, to the best of our knowledge, the first genome-wide map of the genetic control of gene expression in porcine peripheral blood. These results represent an interesting resource for the identification of genetic markers and blood biomarkers associated with variations in immunity traits in pigs, as well as any other complex traits for which blood is an appropriate surrogate tissue.

Computational Models of the Intestinal Environment. 3. The Impact of Cholesterol Content and pH on Mixed Micelle Colloids.

In this study, we use molecular dynamics (MD) and experimental techniques (nephelometry and dynamic light scattering) to investigate the influence of cholesterol content and pH on the colloidal structures that form in the gastrointestinal (GI) tract upon lipid digestion. We demonstrate that the ionization state of the molecular species is a primary driver for the self-assembly of aggregates formed by model bile and therefore should be considered when performing in silico modeling of colloidal drug delivery systems. Additionally, the incorporation of physiological concentrations of cholesterol within the model systems does not affect size, number, shape, or dynamics of the aggregates to a significant degree. The MD data shows a reduction in aggregate size with increasing pH, a preference for glycodeoxycholate (GDX) to occupy the aggregate surface, and that the mixed micellar aggregates are oblate spheroids (disc-like). The results obtained assist in understanding the process by which pH and cholesterol influence self-assembly of mixed micelles within the GI tract. The MD approach provides a platform for investigation of interactions of drugs and formulation excipients with the endogenous contents of the GI tract.

Investigation of the N-Terminus Amino Function of Arg10-Teixobactin.

Teixobactin is a recently described antimicrobial peptide that shows high activity against gram-positive bacteria as well as mycobacterium tuberculosis. Due to both its structure as a head-to-side chain cyclodepsipeptide and its activity, it has attracted the attention of several research groups. In this regard, a large number of analogs with substitutions in both the cycle and the tail has been described. Here, we report the contribution of the N-terminus residue, N-Me-d-Phe, to the activity of Arg10-teixobactin. On the basis of our findings, we conclude that the N-terminus accepts minimum changes but not the presence of long alkyl chains. The presence of a positive charge is a requirement for the activity of the peptide. Furthermore, acylation of the N-terminus leads to total loss of activity.

Comparison of whole-genome (13X) and capture (87X) resequencing methods for SNP and genotype callings.

The number of polymorphisms identified with next-generation sequencing approaches depends directly on the sequencing depth and therefore on the experimental cost. Although higher levels of depth ensure more sensitive and more specific SNP calls, economic constraints limit the increase of depth for whole-genome resequencing (WGS). For this reason, capture resequencing is used for studies focusing on only some specific regions of the genome. However, several biases in capture resequencing are known to have a negative impact on the sensitivity of SNP detection. Within this framework, the aim of this study was to compare the accuracy of WGS and capture resequencing on SNP detection and genotype calling, which differ in terms of both sequencing depth and biases. Indeed, we have evaluated the SNP calling and genotyping accuracy in a WGS dataset (13X) and in a capture resequencing dataset (87X) performed on 11 individuals. The percentage of SNPs not identified due to a sevenfold sequencing depth decrease was estimated at 7.8% using a down-sampling procedure on the capture sequencing dataset. A comparison of the 87X capture sequencing dataset with the WGS dataset revealed that capture-related biases were leading with the loss of 5.2% of SNPs detected with WGS. Nevertheless, when considering the SNPs detected by both approaches, capture sequencing appears to achieve far better SNP genotyping, with about 4.4% of the WGS genotypes that can be considered as erroneous and even 10% focusing on heterozygous genotypes. In conclusion, WGS and capture deep sequencing can be considered equivalent strategies for SNP detection, as the rate of SNPs not identified because of a low sequencing depth in the former is quite similar to SNPs missed because of method biases of the latter. On the other hand, capture deep sequencing clearly appears more adapted for studies requiring great accuracy in genotyping.

Functional genomics reveals that a compact terpene synthase gene family can account for terpene volatile production in apple.

Terpenes are specialized plant metabolites that act as attractants to pollinators and as defensive compounds against pathogens and herbivores, but they also play an important role in determining the quality of horticultural food products. We show that the genome of cultivated apple (Malus domestica) contains 55 putative terpene synthase (TPS) genes, of which only 10 are predicted to be functional. This low number of predicted functional TPS genes compared with other plant species was supported by the identification of only eight potentially functional TPS enzymes in apple 'Royal Gala' expressed sequence tag databases, including the previously characterized apple (E,E)-α-farnesene synthase. In planta functional characterization of these TPS enzymes showed that they could account for the majority of terpene volatiles produced in cv Royal Gala, including the sesquiterpenes germacrene-D and (E)-ß-caryophyllene, the monoterpenes linalool and α-pinene, and the homoterpene (E)-4,8-dimethyl-1,3,7-nonatriene. Relative expression analysis of the TPS genes indicated that floral and vegetative tissues were the primary sites of terpene production in cv Royal Gala. However, production of cv Royal Gala floral-specific terpenes and TPS genes was observed in the fruit of some heritage apple cultivars. Our results suggest that the apple TPS gene family has been shaped by a combination of ancestral and more recent genome-wide duplication events. The relatively small number of functional enzymes suggests that the remaining terpenes produced in floral and vegetative and fruit tissues are maintained under a positive selective pressure, while the small number of terpenes found in the fruit of modern cultivars may be related to commercial breeding strategies.

KIT and melanoma predisposition in pigs: sequence variants and association analysis.

KIT mutations have been detected in different cancer subtypes, including melanoma. The gene also has been extensively studied in farm animals for its prominent role in coat color. The present work aimed at detecting KIT variants in a porcine model of cutaneous melanoma, the melanoblastoma-bearing Libechov Minipig (MeLiM). By sequencing exons and intron borders, 36 SNPs and one indel were identified. Of 10 coding SNPs, three were non-synonymous mutations, likely to affect the protein conformation. A promising variant, located in exon 19 (p.Val870Ala), was genotyped in a MeLiM × Duroc cross, and an association analysis was conducted on several melanoma-related traits. This variant showed a significant association with melanoma development, tumor ulceration and cutaneous invasion. In conclusion, although the KIT gene would not be a major causal gene for melanoma development in pig, its genetic variation could be influencing this trait.

Gene co-expression network analysis for porcine intramuscular fatty acid composition.

In pigs, meat quality depends markedly on the fatty acid (FA) content and composition of the intramuscular fat, which is partly determined by the gene expression in this tissue. The aim of this work was to identify the link between muscle gene expression and its FA composition. In an (Iberian × Duroc) × Duroc backcrossed pig population, we identified modules of co-expressed genes, and correlation analyses were performed for each of them versus the phenotypes, finding four relevant modules. Two of the modules were positively correlated with saturated FAs (SFAs) and monounsaturated FAs (MUFAs), while negatively correlated with polyunsaturated FAs (PUFAs) and the omega-6/omega-3 ratio. The gene-enrichment analysis showed that these modules had over-representation of pathways related with the biosynthesis of unsaturated FAs, the Peroxisome proliferator-activated receptor signalling pathway and FA elongation. The two other relevant modules were positively correlated with PUFA and the n-6/n-3 ratio, but negatively correlated with SFA and MUFA. In this case, they had an over-representation of pathways related with fatty and amino acid degradation, and with oxidative phosphorylation. Using a graphical Gaussian model, we inferred a network of connections between the genes within each module. The first module had 52 genes with 87 connections, and the most connected genes were ADIPOQ, which is related with FA oxidation, and ELOVL6 and FABP4, both involved in FA metabolism. The second module showed 196 genes connected by 263 edges, being FN1 and MAP3K11 the most connected genes. On the other hand, the third module had 161 genes connected by 251 edges and ATG13 was the top neighbouring gene, while the fourth module had 224 genes and 655 connections, and its most connected genes were related with mitochondrial pathways. Overall, this work successfully identified relevant muscle gene networks and modules linked with FA composition, providing further insights on how the physiology of the pigs influences FA composition.

Short communication: Bifidobacterium abundance in the faecal microbiota is strongly associated with milk traits in dairy cattle.

The performance of dairy cows is influenced by the microbial communities hosted within their digestive tract. While the rumen microbiota has long been associated with host phenotypes, the impact of the faecal microbiota remains elusive. In this study, we collected 697 faecal samples from commercial Holstein cows and analysed them with 16S rRNA gene analyses. For each animal, routinely recorded data, i.e., milk yield, fat yield, protein yield, fat content, protein content, and an aggregate production trait (pINEL) based on the French economic dairy index, were available to assess the links between the faecal microbiota and host production. Our findings revealed a strong and significant association between the structure of the bacterial and prokaryote community (ß-diversity) and dairy production. In addition, differential abundance analyses identified 48 genera whose abundances were significantly associated with pINEL, milk, fat and protein yield. Among these genera, the increased abundance of Bifidobacterium, and particularly an amplicon sequence variant with a 16S rRNA V3-V4 gene region identical to B. globosum and B. pseudolongum, was found to be the most important for high-yielding animals. Bifidobacterium seemed to be a potential key member of the bovine faecal microbiota that should be further investigated. Conversely, the p-1088-a5 gut group genus was found more abundant in low-productive cows. In conclusion, this study demonstrates significant associations between the faecal microbiota and the performance of dairy cows at the whole lactation scale. A better understanding of the physiology of the gut microbiota could help to improve dairy cow production.

Characterization of bovine vaginal microbiota using 16S rRNA sequencing: associations with host fertility, longevity, health, and production.

Due to their potential impact on the host's phenotype, organ-specific microbiotas are receiving increasing attention in several animal species, including cattle. Specifically, the vaginal microbiota of ruminants is attracting growing interest, due to its predicted critical role on cows' reproductive functions in livestock contexts. Notably, fertility disorders represent a leading cause for culling, and additional research would help to fill relevant knowledge gaps. In the present study, we aimed to characterize the vaginal microbiota of a large cohort of 1171 female dairy cattle from 19 commercial herds in Northern France. Vaginal samples were collected using a swab and the composition of the microbiota was determined through 16S rRNA sequencing targeting the V3-V4 hypervariable regions. Initial analyses allowed us to define the core bacterial vaginal microbiota, comprising all the taxa observed in more than 90% of the animals. Consequently, four phyla, 16 families, 14 genera and a single amplicon sequence variant (ASV) met the criteria, suggesting a high diversity of bacterial vaginal microbiota within the studied population. This variability was partially attributed to various environmental factors such as the herd, sampling season, parity, and lactation stage. Next, we identified numerous significant associations between the diversity and composition of the vaginal microbiota and several traits related to host's production and reproduction performance, as well as reproductive tract health. Specifically, 169 genera were associated with at least one trait, with 69% of them significantly associated with multiple traits. Among these, the abundances of Negativibacillus and Ruminobacter were positively correlated with the cows' performances (i.e., longevity, production performances). Other genera showed mixed relationships with the phenotypes, such as Leptotrichia being overabundant in cows with improved fertility records and reproductive tract health, but also in cows with lower production levels. Overall, the numerous associations underscored the complex interactions between the vaginal microbiota and its host. Given the large number of samples collected from commercial farms and the diversity of the phenotypes considered, this study marks an initial step towards a better understanding of the intimate relationship between the vaginal microbiota and the dairy cow's phenotypes.

Gut barrier-microbiota imbalances in early life lead to higher sensitivity to inflammation in a murine model of C-section delivery.

BACKGROUND: Most interactions between the host and its microbiota occur at the gut barrier, and primary colonizers are essential in the gut barrier maturation in the early life. The mother-offspring transmission of microorganisms is the most important factor influencing microbial colonization in mammals, and C-section delivery (CSD) is an important disruptive factor of this transfer. Recently, the deregulation of symbiotic host-microbe interactions in early life has been shown to alter the maturation of the immune system, predisposing the host to gut barrier dysfunction and inflammation. The main goal of this study is to decipher the role of the early-life gut microbiota-barrier alterations and its links with later-life risks of intestinal inflammation in a murine model of CSD. RESULTS: The higher sensitivity to chemically induced inflammation in CSD mice is related to excessive exposure to a too diverse microbiota too early in life. This early microbial stimulus has short-term consequences on the host homeostasis. It switches the pup's immune response to an inflammatory context and alters the epithelium structure and the mucus-producing cells, disrupting gut homeostasis. This presence of a too diverse microbiota in the very early life involves a disproportionate short-chain fatty acids ratio and an excessive antigen exposure across the vulnerable gut barrier in the first days of life, before the gut closure. Besides, as shown by microbiota transfer experiments, the microbiota is causal in the high sensitivity of CSD mice to chemical-induced colitis and in most of the phenotypical parameters found altered in early life. Finally, supplementation with lactobacilli, the main bacterial group impacted by CSD in mice, reverts the higher sensitivity to inflammation in ex-germ-free mice colonized by CSD pups' microbiota. CONCLUSIONS: Early-life gut microbiota-host crosstalk alterations related to CSD could be the linchpin behind the phenotypic effects that lead to increased susceptibility to an induced inflammation later in life in mice. Video Abstract.

Analyzing the spatial distribution of PCB concentrations in soils using below-quantification limit data.

Polychlorinated biphenyls (PCBs) are highly toxic environmental pollutants that can accumulate in soils. We consider the problem of explaining and mapping the spatial distribution of PCBs using a spatial data set of 105 PCB-187 measurements from a region in the north of France. A large proportion of our data (35%) fell below a quantification limit (QL), meaning that their concentrations could not be determined to a sufficient degree of precision. Where a measurement fell below this QL, the inequality information was all that we were presented with. In this work, we demonstrate a full geostatistical analysis-bringing together the various components, including model selection, cross-validation, and mapping-using censored data to represent the uncertainty that results from below-QL observations. We implement a Monte Carlo maximum likelihood approach to estimate the geostatistical model parameters. To select the best set of explanatory variables for explaining and mapping the spatial distribution of PCB-187 concentrations, we apply the Akaike Information Criterion (AIC). The AIC provides a trade-off between the goodness-of-fit of a model and its complexity (i.e., the number of covariates). We then use the best set of explanatory variables to help interpolate the measurements via a Bayesian approach, and produce maps of the predictions. We calculate predictions of the probability of exceeding a concentration threshold, above which the land could be considered as contaminated. The work demonstrates some differences between approaches based on censored data and on imputed data (in which the below-QL data are replaced by a value of half of the QL). Cross-validation results demonstrate better predictions based on the censored data approach, and we should therefore have confidence in the information provided by predictions from this method.

Country-level fire perimeter datasets (2001-2021).

Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually.

Quantifying spatial non-stationarity in the relationship between landscape structure and the provision of ecosystem services: An example in the New Zealand hill country.

Knowing how landscape structure affects the provision of ecosystem services (ES) is an important first step toward better landscape planning. Because landscape structure is often heterogenous across space, modelling the relationship between landscape structure and the provision of ES must account for spatial non-stationarity. This paper examines the relationship between landscape structure and the provision of ES using a hill country and steep-land case farm in New Zealand. Indicators derived from land cover and topographical data such as Largest Patch Index (LPI), Contrast Class Edge (CCE), Edge Density (ED), and Terrain slope (SLOPE) were used to examine the landscape's structure and pattern. Measures of pasture productivity, soil erosion control, and water supply were derived with InVEST tools and spatial analysis in a GIS. Multiscale Geographically Weighted Regression (MGWR) was used to evaluate the relationship between indicators of landscape structure and the provisioning of ES. Other regression models, including Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR), were carried out to evaluate the performance of MGWR. Results showed that landscape patterns significantly affect the supply of all mapped ES, and this varies across the landscape, dependent on the pattern of topographical features and land cover pattern and structure. MWGR outperformed other OLS and GWR in terms of explanatory power of the ES determinants and had a better ability to deal with the presence of spatial autocorrelation. Spatially and quantitatively detailed variations of the relationship between landscape structure and the provision of ES provide a scientific basis to inform the design of sustainable multifunctional landscapes. Information derived from this analysis can be used for spatial planning of farmed landscapes to promote multiple ES which meet multiple sustainable development objectives.

In vivo delivery of plasmid DNA by lipid nanoparticles: the influence of ionizable cationic lipids on organ-selective gene expression.

Ionizable cationic lipids play a critical role in developing new gene therapies for various biomedical applications, including COVID-19 vaccines. However, it remains unclear whether the formulation of lipid nanoparticles (LNPs) using DLin-MC3-DMA, an optimized ionizable lipid clinically used for small interfering RNA (siRNA) therapy, also facilitates high liver-selective transfection of other gene therapies such as plasmid DNA (pDNA). Here we report the first investigation into pDNA transfection efficiency in different mouse organs after intramuscular and intravenous administration of lipid nanoparticles (LNPs) where DLin-MC3-DMA, DLin-KC2-DMA or DODAP are used as the ionizable cationic lipid component of the LNP. We discovered that these three benchmark lipids previously developed for siRNA delivery followed an unexpected characteristic rank order in gene expression efficiency when utilized for pDNA. In particular, DLin-KC2-DMA facilitated higher in vivo pDNA transfection than DLin-MC3-DMA and DODAP, possibly due to its head group pKa and lipid tail structure. Interestingly, LNPs formulated with either DLin-KC2-DMA or DLin-MC3-DMA exhibited significantly higher in vivo protein production in the spleen than in the liver. This work sheds light on the importance of the choice of ionizable cationic lipid and nucleic acid cargo for organ-selective gene expression. The study also provides a new design principle towards the formulation of more effective LNPs for biomedical applications of pDNA, such as gene editing, vaccines and immunotherapies.

Interaction with biliary and pancreatic fluids drives supersaturation and drug absorption from lipid-based formulations of low (saquinavir) and high (fenofibrate) permeability poorly soluble drugs.

Drug absorption from lipid-based formulations (LBFs) in the gastrointestinal (GI) tract is the result of a series of processes, including formulation dispersion, interaction with biliary and pancreatic secretions, drug solubilisation and supersaturation, and finally intestinal permeability. Optimal formulation design is dependent on a good understanding of the limitations to, and drivers of, absorption, but for LBFs the complexity of these processes makes data interpretation complex. The current study has re-examined a previous in vitro digestion-in situ perfusion model to increase physiological relevance and has used this model to examine drug absorption from LBFs. The composition of rat bile and jejunal fluid was also characterised to identify in vivo-relevant conditions. Digestion was initiated using rat bile/pancreatic fluid and the formulation and digestive enzymes mixed immediately prior to entry into the jejunum (allowing dilution/digestion to occur at the absorptive site). These conditions were employed to study drug absorption from LBFs of high (fenofibrate, FFB) and low (saquinavir, SQV) permeability compounds. The impact of polymeric precipitation inhibitors (PPIs) was also evaluated. For FFB, supersaturation, initiated by formulation interaction with biliary/pancreatic fluids, appeared to drive absorption and the addition of the PPIs poly(glycidyl methacrylate) (PPGAE) and hydroxypropylmethyl cellulose (HPMC), reduced drug precipitation, increased FFB supersaturation and increased absorption from a Type IV LBF of FFB. For a Type IIIB LBF however, PPIs were ineffective at increasing absorption. The impact of PPIs on the absorption of a less permeable drug, SQV, was similarly evaluated and again drug absorption appeared to be related to the extent of supersaturation, although in this case PPI were unable to promote absorption. For both FFB and SQV, drug absorption patterns obtained with the in vitro digestion-in situ perfusion mode, correlated well with in vitro supersaturation data and in vivo drug exposure data from oral bioavailability studies. The data are consistent with a mode of drug absorption where rapid dilution of LBFs with biliary and pancreatic secretions at the absorptive site in the upper small intestine drives transient supersaturation, that supersaturation is a significant driver of drug absorption for both low and high permeability drugs, and that PPIs delay drug precipitation, enhance supersaturation and promote drug absorption in a drug and formulation specific manner.

Super-Cationic Peptide Dendrimers-Synthesis and Evaluation as Antimicrobial Agents.

Microbial infections are a major public health concern. Antimicrobial peptides (AMPs) have been demonstrated to be a plausible alternative to the current arsenal of drugs that has become inefficient due to multidrug resistance. Herein we describe a new AMP family, namely the super-cationic peptide dendrimers (SCPDs). Although all members of the series exert some antibacterial activity, we propose that special attention should be given to (KLK)2KLLKLL-NH2 (G1KLK-L2KL2), which shows selectivity for Gram-negative bacteria and virtually no cytotoxicity in HepG2 and HEK293. These results reinforce the validity of the SCPD family as a valuable class of AMP and support G1KLK-L2KL2 as a strong lead candidate for the future development of an antibacterial agent against Gram-negative bacteria.