Neuropilin 2/Plexin-A3 receptors regulate the functional connectivity and the excitability in the layers 4 and 5 of the cerebral cortex

The functions of cortical networks are progressively established during development by series of events shaping the neuronal connectivity. Synaptic elimination, which consists of removing the supernumerary connections generated during the earlier stages of cortical development, is one of the latest stages in neuronal network maturation. The semaphorin 3F coreceptors neuropilin 2 (Nrp2) and plexin-A3 (PlxnA3) may play an important role in the functional maturation of the cerebral cortex by regulating the excess dendritic spines on cortical excitatory neurons. Yet, the identity of the connections eliminated under the control of Nrp2/PlxnA3 signaling is debated, and the importance of this synaptic refinement for cortical functions remains poorly understood. Here, we show that Nrp2/PlxnA3 controls the spine densities in layer 4 (L4) and on the apical dendrite of L5 neurons of the sensory and motor cortices. Using a combination of neuroanatomical, ex vivo electrophysiology, and in vivo functional imaging techniques in Nrp2 and PlxnA3 KO mice of both sexes, we disprove the hypothesis that Nrp2/PlxnA3 signaling is required to maintain the ectopic thalamocortical connections observed during embryonic development. We also show that the absence of Nrp2/PlxnA3 signaling leads to the hyperexcitability and excessive synchronization of the neuronal activity in L5 and L4 neuronal networks, suggesting that this system could participate in the refinement of the recurrent corticocortical connectivity in those layers. Altogether, our results argue for a role of semaphorin–Nrp2/PlxnA3 signaling in the proper maturation and functional connectivity of the cerebral cortex, likely by controlling the refinement of recurrent corticocortical connections

Prevalence of CTX-M β-Lactamases Producing Multidrug Resistant Escherichia coli and Klebsiella pneumoniae among Patients Attending Bir Hospital, Nepal

The emergence of multidrug resistant (MDR) bacteria which is attributable to extended spectrum β-lactamases (ESBLs) production of CTX-M types is an obvious problem worldwide. This study is aimed at determining the prevalence of CTX-M β-lactamases producing multidrug resistant Escherichia coli and Klebsiella pneumoniae among patients attending Bir Hospital. A cross-sectional study was conducted between April and September 2019 at Bir Hospital, Kathmandu, and Department of Microbiology, National College, Kathmandu, Nepal. A total of 5,690 different clinical specimens were subjected to cultural, microscopic, and biochemical analyses for the identification of the isolates. Antimicrobial susceptibility testing of the isolates was done, and MDR isolates were selected and processed for further ESBL confirmation by the combination disks method. All confirmed ESBL isolates were screened for CTX-M type β-lactamases (blaCTX-M) by PCR. Of the total 345 isolates (227 Escherichia coli and 118 Klebsiella pneumoniae), 232 were MDR. All 232 (67.24%) MDR isolates were suspected as ESBL producers on the screening test. However, on the phenotypic test, 135 (58.18%) of total MDR bacteria were confirmed as ESBL producers with the highest proportion in K. pneumoniae (59.37%). The major source of ESBL producers was urine. ESBL producing isolates were mostly identified from outpatients and patients belonging to age group 41-60. Gentamicin was found to be effective against ESBL producers. The prevalence of blaCTX-M was (89.62%) with the highest frequency for E. coli (93.81%). High prevalence of ESBL of CTX-M types among MDR E. coli and K. pneumoniae was detected from clinical specimens of patients in Bir Hospital. This study warrants the need for the judicious use of antibiotics as well as emphasize the use of modern diagnostic tools for the early detection of MDR and ESBL producers to curb the emergence and spread of MDR and ESBL producing bacteria in the clinical settings of Nepal

Changes in gastrointestinal microbial communities influence HIV-specific CD8+ T-cell responsiveness to immune checkpoint blockade.

ObjectivesThe aim of this study was to examine the relationship between gut microbial communities in HIV-infected individuals on suppressive antiretroviral therapy (cART), and the peripheral HIV-Gag-specific CD8 T-cell responses before and after ex-vivo immune checkpoint blockade (ICB).DesignThirty-four HIV-seropositive, 10 HIV-seronegative and 12 HIV-seropositive receiving faecal microbiota transplant (FMT) participants were included. Gut microbial communities, peripheral and gut associated negative checkpoint receptors (NCRs) and peripheral effector functions were assessed.MethodsBacterial 16s rRNA sequencing for gut microbiome study and flow-based assays for peripheral and gut NCR and their cognate ligand expression, including peripheral HIV-Gag-specific CD8 T-cell responses before and after ex-vivo anti-PD-L1 and anti-TIGIT ICB were performed.ResultsFusobacteria abundance was significantly higher in HIV-infected donors compared to uninfected controls. In HIV-infected participants receiving Fusobacteria-free FMT, Fusobacteria persisted up to 24 weeks in stool post FMT. PD-1 TIGIT and their ligands were expanded in mucosal vs. peripheral T cells and dendritic cells, respectively. PD-L1 and TIGIT blockade significantly increased the magnitude of peripheral anti-HIV-Gag-specific CD8 T-cell responses. Higher gut Fusobacteria abundance was associated with lower magnitude of peripheral IFN-γ+ HIV-Gag-specific CD8 T-cell responses following ICB.ConclusionThe gut colonization of Fusobacteria in HIV infection is persistent and may influence anti-HIV T-cell immunity to PD-1 or TIGIT blockade. Strategies modulating Fusobacteria colonization may elicit a favourable mucosal immune landscape to enhance the efficacy of ICB for HIV cure

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.