Cyclic di-GMP: second messenger extraordinaire

Cyclic dinucleotides (CDNs) are highly versatile signalling molecules that control various important biological processes in bacteria. The best-studied example is cyclic di-GMP (c-di-GMP). Known since the late 1980s, it is now recognized as a near-ubiquitous second messenger that coordinates diverse aspects of bacterial growth and behaviour, including motility, virulence, biofilm formation and cell cycle progression. In this Review, we discuss important new insights that have been gained into the molecular principles of c-di-GMP synthesis and degradation, which are mediated by diguanylate cyclases and c-di-GMP-specific phosphodiesterases, respectively, and the cellular functions that are exerted by c-di-GMP-binding effectors and their diverse targets. Finally, we provide a short overview of the signalling versatility of other CDNs, including c-di-AMP and cGMP-AMP (cGAMP)

A moonlighting enzyme imposes second messenger bistability to drive lifestyle decisions in E. coli.

Bacteria preferentially colonize surfaces and air-liquid interfaces as matrix embedded communities called biofilms. Biofilms exhibit specific physiological properties, including general stress tolerance, increased antibiotic recalcitrance and tolerance against phagocytic clearance. Together this largely accounts for increased biofilm persistence, chronic infections and infection relapses. One of the principle regulators of biofilm formation is c-di-GMP, a bacterial second messenger controlling various cellular processes. Cellular levels of c-di-GMP are controlled by two antagonistic enzyme families, diguanylate cyclases and phosphodiesterases. But despite the identification and characterization of an increasing number of components of the c-di-GMP network in different bacterial model organisms, details of c-di- GMP mediated decision-making have remained unclear. In particular, how cells shuttle between specific c-di-GMP regimes at the population and single cell level is largely unknown and moreover how these transitions are deterministically made in time and space, given that bacterial networks of diguanylate cyclases and phosphodiesterases show a high degree of complexity. Here we describe a novel mechanism regulating c-di-GMP mediated biofilm formation in E. coli. This mechanism relies on the bistable expression of a key phosphodiesterase that acts both as catalyst for c- di-GMP degradation and as a transcription factor promoting its own production. Bistability results from two interconnected positive feedback loops operating on the catalytic and gene expression level. Based on genetic, structural and biochemical analyses we postulate a simple substrate-induced switch mechanism through which this enzyme can sense changing concentration of c-di-GMP and convert this information into a bistable c-di-GMP response. This mechanism may explain how cellular heterogeneity of small signaling molecules is generated in bacteria and used as a bet hedging strategy for important lifestyle transitions

The Pion-Nucleon Form Factor From QCD Sum Rules

QCD sum rules are used to calculate the $q^2$ dependence of the $\pi NN$ coupling $g_{\pi NN} (q^2)$ in the spacelike region 0.5 \ {\mbox{GeV}}^2 \lesssim q^2 \lesssim 1.5\ {\mbox{GeV}}^2. We study the Borel sum rule for the three point function of one pseudoscalar and two nucleon currents up to order four in the operator product expansion. The Borel transform is performed with respect to the nucleon momenta, whereas the momentum $q^2$ of the pseudoscalar vertex is kept fixed at spacelike values. The results can be well fitted using a monopole form with a cutoff mass of about $\Lambda_\pi \approx 800 \ {\mbox{MeV}}.Comment: 13 pages (REVTEX), 6 figures as 5 postscript files (as fig.uu tarred, compressed, uudecoded

Correction to: A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer’s disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity

The IPDGC (The International Parkinson Disease Genomics Consortium) and EADB (Alzheimer Disease European DNA biobank) are listed correctly as an author to the article, however, they were incorrectly listed more than once

Machine learning in Alzheimer’s disease genetics

: Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer's disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics

Recovery of dialysis patients with COVID-19 : health outcomes 3 months after diagnosis in ERACODA

Background. Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis. Methods. We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression. Results. In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome. Conclusions. Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele