Bacterial and Archaeal Specific-Predation in the North Atlantic Basin

Stable isotope probing (SIP) was used to track prokaryotic and eukaryotic carbon uptake along a meridional transect (Long. 52°W) in the North Atlantic to assess if 13C-resource partitioning between bacteria and archaea and 13C-labeled eukaryotic predators could be detected. One-liter SIP microcosms were amended with 13C-acetate or 13C-urea and incubated for 48 h. Our data indicated archaea often outcompeted bacteria for 13C-urea while both archaea and bacteria could incorporate 13C-acetate. This 13C label could also be tracked into eukaryotic microbes. The largest number of 13C-labeled eukaryotic OTUs, and the greatest percentage of eukaryotic 13C signal, were observed in conjunction with both archaeal and bacterial 13C incorporation, suggesting that most eukaryotic predators do not distinguish between archaeal and bacterial prey. However, other 13C-eukaryotic OTUs were exclusively associated with either 13C-archaeal or 13C-bacterial OTUs. These archaeal-specific and bacterial-specific 13C-eukaryotic OTUs were related to known bactivorous predators including Ancyromonas, Amastigomonas, Cafeteria, and Caecitellus. Our SIP findings suggest both resource partitioning between bacteria and TACK (Thaumarchaeota, Aigarchaeota, Crenarchaeota, and Korarchaeota) archaea and selective predation by eukaryotic predators. Determining the equalizing mechanisms for co-existence in the marine environment can help map predator/prey interactions to better estimate carbon flow in the deep ocean

Loss-of-function mutations in TNFAIP3 leading to A20 haploinsufficiency cause an early-onset autoinflammatory disease

Systemic autoinflammatory diseases are driven by abnormal activation of innate immunity. Herein we describe a new disease caused by high-penetrance heterozygous germline mutations in TNFAIP3, which encodes the NF-B regulatory protein A20, in six unrelated families with early-onset systemic inflammation. The disorder resembles Behçet\u27s disease, which is typically considered a polygenic disorder with onset in early adulthood. A20 is a potent inhibitor of the NF-B signaling pathway. Mutant, truncated A20 proteins are likely to act through haploinsufficiency because they do not exert a dominant-negative effect in overexpression experiments. Patient-derived cells show increased degradation of IBα and nuclear translocation of the NF-B p65 subunit together with increased expression of NF-B-mediated proinflammatory cytokines. A20 restricts NF-B signals via its deubiquitinase activity. In cells expressing mutant A20 protein, there is defective removal of Lys63-linked ubiquitin from TRAF6, NEMO and RIP1 after stimulation with tumor necrosis factor (TNF). NF-B-dependent proinflammatory cytokines are potential therapeutic targets for the patients with this disease

Development of a consensus core dataset in juvenile dermatomyositis for clinical use to inform research

Objectives This study aimed to develop consensus on an internationally agreed dataset for juvenile dermatomyositis (JDM), designed for clinical use, to enhance collaborative research and allow integration of data between centres. Methods A prototype dataset was developed through a formal process that included analysing items within existing databases of patients with idiopathic inflammatory myopathies. This template was used to aid a structured multistage consensus process. Exploiting Delphi methodology, two web-based questionnaires were distributed to healthcare professionals caring for patients with JDM identified through email distribution lists of international paediatric rheumatology and myositis research groups. A separate questionnaire was sent to parents of children with JDM and patients with JDM, identified through established research networks and patient support groups. The results of these parallel processes informed a face-to-face nominal group consensus meeting of international myositis experts, tasked with defining the content of the dataset. This developed dataset was tested in routine clinical practice before review and finalisation. Results A dataset containing 123 items was formulated with an accompanying glossary. Demographic and diagnostic data are contained within form A collected at baseline visit only, disease activity measures are included within form B collected at every visit and disease damage items within form C collected at baseline and annual visits thereafter. Conclusions Through a robust international process, a consensus dataset for JDM has been formulated that can capture disease activity and damage over time. This dataset can be incorporated into national and international collaborative efforts, including existing clinical research databases