TTAPE-Me dye is not selective to cardiolipin and binds to common anionic phospholipids nonspecifically

Identification, visualization, and quantitation of cardiolipin (CL) in biological membranes is of great interest because of the important structural and physiological roles of this lipid. Selective fluorescent detection of CL using noncovalently bound fluorophore 1,1,2,2-tetrakis[4-(2-trimethylammonioethoxy)-phenylethene (TTAPE-Me) has been recently proposed. However, this dye was only tested on wild-type mitochondria or liposomes containing negligible amounts of other anionic lipids, such as phosphatidylglycerol (PG) and phosphatidylserine (PS). No clear preference of TTAPE-Me for binding to CL compared to PG and PS was found in our experiments on artificial liposomes, Escherichia coli inside-out vesicles, or Saccharomyces cerevisiae mitochondria in vitro or in situ, respectively. The shapes of the emission spectra for these anionic phospholipids were also found to be indistinguishable. Thus, TTAPE-Me is not suitable for detection, visualization, and localization of CL in the presence of other anionic lipids present in substantial physiological amounts. Our experiments and complementary molecular dynamics simulations suggest that fluorescence intensity of TTAPE-Me is regulated by dynamic equilibrium between emitting dye aggregates, stabilized by unspecific but thermodynamically favorable electrostatic interactions with anionic lipids, and nonemitting dye monomers. These results should be taken into consideration when interpreting past and future results of CL detection and localization studies with this probe in vitro and in vivo. Provided methodology emphasizes minimal experimental requirements, which should be considered as a guideline during the development of novel lipid-specific probes

Phospholipid distribution in the cytoplasmic membrane of Gram-negative bacteria is highly asymmetric, dynamic, and cell shape-dependent

© 2020 The Authors. The distribution of phospholipids across the inner membrane (IM) of Gram-negative bacteria is unknown. We demonstrate that the IMs of Escherichia coli and Yersinia pseudotuberculosis are asymmetric, with a 75%/25% (cytoplasmic/periplasmic leaflet) distribution of phosphatidylethanolamine (PE) in rod-shaped cells and an opposite distribution in E. coli filamentous cells. In initially filamentous PE-lacking E. coli cells, nascent PE appears first in the periplasmic leaflet. As the total PE content increases from nearly zero to 75%, cells progressively adopt a rod shape and PE appears in the cytoplasmic leaflet of the IM. The redistribution of PE influences the distribution of the other lipids between the leaflets. This correlates with the tendency of PE and cardiolipin to regulate antagonistically lipid order of the bilayer. The results suggest that PE asymmetry is metabolically controlled to balance temporally the net rates of synthesis and translocation, satisfy envelope growth capacity, and adjust bilayer chemical and physical properties

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

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.