The role of the complement system in traumatic brain injury: a review

Traumatic brain injury (TBI) is an important cause of disability and mortality in the western world. While the initial injury sustained results in damage, it is the subsequent secondary cascade that is thought to be the significant determinant of subsequent outcomes. The changes associated with the secondary injury do not become irreversible until some time after the start of the cascade. This may present a window of opportunity for therapeutic interventions aiming to improve outcomes subsequent to TBI. A prominent contributor to the secondary injury is a multifaceted inflammatory reaction. The complement system plays a notable role in this inflammatory reaction; however, it has often been overlooked in the context of TBI secondary injury. The complement system has homeostatic functions in the uninjured central nervous system (CNS), playing a part in neurodevelopment as well as having protective functions in the fully developed CNS, including protection from infection and inflammation. In the context of CNS injury, it can have a number of deleterious effects, evidence for which primarily comes not only from animal models but also, to a lesser extent, from human post-mortem studies. In stark contrast to this, complement may also promote neurogenesis and plasticity subsequent to CNS injury. This review aims to explore the role of the complement system in TBI secondary injury, by examining evidence from both clinical and animal studies. We examine whether specific complement activation pathways play more prominent roles in TBI than others. We also explore the potential role of complement in post-TBI neuroprotection and CNS repair/regeneration. Finally, we highlight the therapeutic potential of targeting the complement system in the context of TBI and point out certain areas on which future research is needed

Food for pollinators: quantifying the nectar and pollen resources of urban flower meadows

Planted meadows are increasingly used to improve the biodiversity and aesthetic amenity value of urban areas. Although many ‘pollinator-friendly’ seed mixes are available, the floral resources these provide to flower-visiting insects, and how these change through time, are largely unknown. Such data are necessary to compare the resources provided by alternative meadow seed mixes to each other and to other flowering habitats. We used quantitative surveys of over 2 million flowers to estimate the nectar and pollen resources offered by two exemplar commercial seed mixes (one annual, one perennial) and associated weeds grown as 300m2 meadows across four UK cities, sampled at six time points between May and September 2013. Nectar sugar and pollen rewards per flower varied widely across 65 species surveyed, with native British weed species (including dandelion, Taraxacum agg.) contributing the top five nectar producers and two of the top ten pollen producers. Seed mix species yielding the highest rewards per flower included Leontodon hispidus, Centaurea cyanus and C. nigra for nectar, and Papaver rhoeas, Eschscholzia californica and Malva moschata for pollen. Perennial meadows produced up to 20x more nectar and up to 6x more pollen than annual meadows, which in turn produced far more than amenity grassland controls. Perennial meadows produced resources earlier in the year than annual meadows, but both seed mixes delivered very low resource levels early in the year and these were provided almost entirely by native weeds. Pollen volume per flower is well predicted statistically by floral morphology, and nectar sugar mass and pollen volume per unit area are correlated with flower counts, raising the possibility that resource levels can be estimated for species or habitats where they cannot be measured directly. Our approach does not incorporate resource quality information (for example, pollen protein or essential amino acid content), but can easily do so when suitable data exist. Our approach should inform the design of new seed mixes to ensure continuity in floral resource availability throughout the year, and to identify suitable species to fill resource gaps in established mixes

Diurnal and Circadian Rhythms in the Tomato Transcriptome and Their Modulation by Cryptochrome Photoreceptors

BACKGROUND: Circadian clocks are internal molecular time-keeping mechanisms that provide living organisms with the ability to adjust their growth and physiology and to anticipate diurnal environmental changes. Circadian clocks, without exception, respond to light and, in plants, light is the most potent and best characterized entraining stimulus. The capacity of plants to respond to light is achieved through a number of photo-perceptive proteins including cryptochromes and phytochromes. There is considerable experimental evidence demonstrating the roles of photoreceptors in providing light input to the clock. METHODOLOGY: In order to identify genes regulated by diurnal and circadian rhythms, and to establish possible functional relations between photoreceptors and the circadian clock in tomato, we monitored the temporal transcription pattern in plants entrained to long-day conditions, either by large scale comparative profiling, or using a focused approach over a number of photosensory and clock-related genes by QRT-PCR. In parallel, focused transcription analyses were performed in cry1a- and in CRY2-OX tomato genotypes. CONCLUSIONS: We report a large series of transcript oscillations that shed light on the complex network of interactions among tomato photoreceptors and clock-related genes. Alteration of cryptochrome gene expression induced major changes in the rhythmic oscillations of several other gene transcripts. In particular, over-expression of CRY2 had an impact not only on day/night fluctuations but also on rhythmicity under constant light conditions. Evidence was found for widespread diurnal oscillations of transcripts encoding specific enzyme classes (e.g. carotenoid biosynthesis enzymes) as well as for post-transcriptional diurnal and circadian regulation of the CRY2 transcript

Functional materials discovery using energy–structure–function maps

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal–organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy–structure–function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy–structure–function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties

Targeted, high-resolution RNA sequencing of non-coding genomic regions associated with neuropsychiatric functions

The human brain is one of the last frontiers of biomedical research. Genome-wide association studies (GWAS) have succeeded in identifying thousands of haplotype blocks associated with a range of neuropsychiatric traits, including disorders such as schizophrenia, Alzheimer's and Parkinson's disease. However, the majority of single nucleotide polymorphisms (SNPs) that mark these haplotype blocks fall within non-coding regions of the genome, hindering their functional validation. While some of these GWAS loci may contain cis-acting regulatory DNA elements such as enhancers, we hypothesized that many are also transcribed into non-coding RNAs that are missing from publicly available transcriptome annotations. Here, we use targeted RNA capture ('RNA CaptureSeq') in combination with nanopore long-read cDNA sequencing to transcriptionally profile 1,023 haplotype blocks across the genome containing non-coding GWAS SNPs associated with neuropsychiatric traits, using post-mortem human brain tissue from three neurologically healthy donors. We find that the majority (62%) of targeted haplotype blocks, including 13% of intergenic blocks, are transcribed into novel, multi-exonic RNAs, most of which are not yet recorded in GENCODE annotations. We validated our findings with short-read RNA-seq, providing orthogonal confirmation of novel splice junctions and enabling a quantitative assessment of the long-read assemblies. Many novel transcripts are supported by independent evidence of transcription including cap analysis of gene expression (CAGE) data and epigenetic marks, and some show signs of potential functional roles. We present these transcriptomes as a preliminary atlas of non-coding transcription in human brain that can be used to connect neurological phenotypes with gene expression