CD4 +

Vaccination strategies incorporating the immunodominant HLA-A2-restricted HER2/neu-derived peptide 369-377 (HER2(369-377)) are increasingly utilized in HER2/neu-expressing cancer patients. The failure of post-vaccination HER2(369-377)-specific CD8(+) T cells to recognize HLA-A2(pos)HER2/neu-expressing cells in vitro, however, has been attributed to impaired MHC class I/HLA-A2 presentation observed in HER2/neu-overexpressing tumors. We reconcile this controversy by demonstrating that HER2(369-377) is directly recognized by high functional-avidityHER2(369-377)-specific CD8(+) T cells—either genetically modified to express a novel HER2(369-377)-TCR or sensitized using HER2(369-377)-pulsed type 1-polarized dendritic cells (DC1)—on class I-abundant HER2(low), but not class I-deficient HER2(high), cancer cells. Importantly, a critical cooperation between CD4(+) T-helper type-1 (Th1) cytokines IFNγ/TNFα and HER2/neu-targeted antibody trastuzumab is necessary to restore class I expression in HER2(high) cancers, thereby facilitating recognition and lysis of these cells by HER2(369-377)-specific CD8(+) T cells. Concomitant induction of PD-L1 on HER2/neu-expressing cells by IFNγ/TNF and trastuzumab, however, has minimal impact on DC1-sensitized HER2(369-377)-CD8(+) T cell-mediated cytotoxicity. Although activation of EGFR and HER3 signaling significantly abrogates IFNγ/TNFα and trastuzumab-induced class I restoration, EGFR/HER3 receptor blockade rescues class I expression and ensuing HER2(369-377)-CD8(+) cytotoxicity of HER2/neu-expressing cells. Thus, combinations of CD4(+) Th1 immune interventions and multivalent targeting of HER family members may be required for optimal anti-HER2/neuCD8(+) T cell-directed immunotherapy

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.