Mycobacterium tuberculosis persists within macrophages in an arrested phagosome and depends upon necrosis to elude immunity and disseminate. Although apoptosis of M. tuberculosis-infected macrophages ...is associated with reduced bacterial growth, the bacteria are relatively resistant to other forms of death, leaving the mechanism underlying this observation unresolved. We find that after apoptosis, M. tuberculosis-infected macrophages are rapidly taken up by uninfected macrophages through efferocytosis, a dedicated apoptotic cell engulfment process. Efferocytosis of M. tuberculosis sequestered within an apoptotic macrophage further compartmentalizes the bacterium and delivers it along with the apoptotic cell debris to the lysosomal compartment. M. tuberculosis is killed only after efferocytosis, indicating that apoptosis itself is not intrinsically bactericidal but requires subsequent phagocytic uptake and lysosomal fusion of the apoptotic body harboring the bacterium. While efferocytosis is recognized as a constitutive housekeeping function of macrophages, these data indicate that it can also function as an antimicrobial effector mechanism.
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► Apoptosis occurs after virulent Mycobacterium tuberculosis (Mtb) infection ► Mtb-infected dead cells are engulfed by uninfected macrophages via efferocytosis ► Efficient maturation of the bacteria-containing efferocytic phagosome kills Mtb ► Efferocytosis is an antibacterial effector mechanism both in vitro and in vivo
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
While a third of the world carries the burden of tuberculosis, disease control has been hindered by a lack of tools, including a rapid, point-of-care diagnostic and a protective vaccine. In many ...infectious diseases, antibodies (Abs) are powerful biomarkers and important immune mediators. However, in Mycobacterium tuberculosis (Mtb) infection, a discriminatory or protective role for humoral immunity remains unclear. Using an unbiased antibody profiling approach, we show that individuals with latent tuberculosis infection (Ltb) and active tuberculosis disease (Atb) have distinct Mtb-specific humoral responses, such that Ltb infection is associated with unique Ab Fc functional profiles, selective binding to FcγRIII, and distinct Ab glycosylation patterns. Moreover, compared to Abs from Atb, Abs from Ltb drove enhanced phagolysosomal maturation, inflammasome activation, and, most importantly, macrophage killing of intracellular Mtb. Combined, these data point to a potential role for Fc-mediated Ab effector functions, tuned via differential glycosylation, in Mtb control.
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•Individuals with latent and active TB infection have divergent humoral signatures•Antibodies in latent TB infection have enhanced Fc effector profiles•Antibody glycosylation patterns can discriminate between latent and active TB•Antibodies in latent TB infection drive macrophages to kill intracellular bacteria
Individuals with active and latent tuberculosis (TB) infections can be distinguished by the type of antibodies they produce, pointing toward an important and unappreciated contribution from humoral immunity in controlling chronic TB.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Variability in bacterial sterilization is a key feature of Mycobacterium tuberculosis (Mtb) disease. In a population of human macrophages, there are macrophages that restrict Mtb growth and those ...that do not. However, the sources of heterogeneity in macrophage state during Mtb infection are poorly understood. Here, we perform RNAseq on restrictive and permissive macrophages and reveal that the expression of genes involved in GM-CSF signaling discriminates between the two subpopulations. We demonstrate that blocking GM-CSF makes macrophages more permissive of Mtb growth while addition of GM-CSF increases bacterial control. In parallel, we find that the loss of bacterial control that occurs in HIV-Mtb coinfected macrophages correlates with reduced GM-CSF secretion. Treatment of coinfected cells with GM-CSF restores bacterial control. Thus, we leverage the natural variation in macrophage control of Mtb to identify a critical cytokine response for regulating Mtb survival and identify components of the antimicrobial response induced by GM-CSF.
Many bacterial pathogens of plants and animals use a type III secretion system to deliver diverse virulence-associated 'effector' proteins into the host cell. The mechanisms by which these effectors ...act are mostly unknown; however, they often promote disease by suppressing host immunity. One type III effector, AvrPtoB, expressed by the plant pathogen Pseudomonas syringae pv. tomato, has a carboxy-terminal domain that is an E3 ubiquitin ligase. Deletion of this domain allows an amino-terminal region of AvrPtoB (AvrPtoB1-387) to be detected by certain tomato varieties leading to immunity-associated programmed cell death. Here we show that a host kinase, Fen, physically interacts with AvrPtoB1-387 and is responsible for activating the plant immune response. The AvrPtoB E3 ligase specifically ubiquitinates Fen and promotes its degradation in a proteasome-dependent manner. This degradation leads to disease susceptibility in Fen-expressing tomato lines. Various wild species of tomato were found to exhibit immunity in response to AvrPtoB1-387 and not to full-length AvrPtoB. Thus, by acquiring an E3 ligase domain, AvrPtoB has thwarted a highly conserved host resistance mechanism.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The activation of an immune response in tomato (Solanum lycopersicum) against Pseudomonas syringae relies on the recognition of E3 ligase—deficient forms of AvrPtoB by the host protein kinase, Fen. ...To investigate the mechanisms by which Fen-mediated immunity is regulated, we characterize in this study a Fen-interacting protein, Fni3, and its cofactor, S. lycoperiscum Uev (Suv). Fni3 encodes a homolog of the Ubc13-type ubiquitin-conjugating enzyme that catalyzes exclusively Lys-63—linked ubiquitination, whereas Suv is a ubiquitin-conjugating enzyme variant. The C-terminal region of Fen was necessary for interaction with Fni3, and this interaction was required for cell death triggered by overexpression of Fen in Nicotiana benthamiana leaves. Fni3 was shown to be an active E2 enzyme, but Suv displayed no ubiquitin-conjugating activity; Fni3 and Suv together directed Lys-63—linked ubiquitination. Decreased expression of Fni3, another tomato Ubc13 homolog, Sl-Ubc13-2, or Suv in N. benthamiana leaves diminished cell death associated with Fen-mediated immunity and cell death elicited by several other resistance (R) proteins and their cognate effectors. We also discovered that coexpression of Fen and other R proteins/effectors with a Fni3 mutant that is compromised for ubiquitin-conjugating activity diminished the cell death. These results suggest that Fni3/Sl-Ubc13-2 and Suv regulate the immune response mediated by Fen and other R proteins through Lys-63—linked ubiquitination.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Diffuse large B cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is a clinically and genetically heterogeneous disease that is further classified into transcriptionally defined ...activated B cell (ABC) and germinal center B cell (GCB) subtypes. We carried out a comprehensive genetic analysis of 304 primary DLBCLs and identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data. We integrated these genetic drivers using consensus clustering and identified five robust DLBCL subsets, including a previously unrecognized group of low-risk ABC-DLBCLs of extrafollicular/marginal zone origin; two distinct subsets of GCB-DLBCLs with different outcomes and targetable alterations; and an ABC/GCB-independent group with biallelic inactivation of TP53, CDKN2A loss, and associated genomic instability. The genetic features of the newly characterized subsets, their mutational signatures, and the temporal ordering of identified alterations provide new insights into DLBCL pathogenesis. The coordinate genetic signatures also predict outcome independent of the clinical International Prognostic Index and suggest new combination treatment strategies. More broadly, our results provide a roadmap for an actionable DLBCL classification.
There is increasing evidence that phenotypically drug-resistant bacteria may be important determinants of antibiotic treatment failure. Using high-throughput imaging, we defined distinct ...subpopulations of mycobacterial cells that exhibit heritable but semi-stable drug resistance. These subpopulations have distinct transcriptional signatures and growth characteristics at both bulk and single-cell levels, which are also heritable and semi-stable. We find that the mycobacterial histone-like protein HupB is required for the formation of these subpopulations. Using proteomic approaches, we further demonstrate that HupB is posttranslationally modified by lysine acetylation and lysine methylation. Mutation of a single posttranslational modification site specifically abolishes the formation of one of the drug-resistant subpopulations of cells, providing the first evidence in prokaryotes that posttranslational modification of a bacterial nucleoid-associated protein may epigenetically regulate cell state.
Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease that largely arises from antigen-exposed B-cells that transit through the germinal center (GC). DLBCL is further classified into ...transcriptional subtypes - activated B-cell (ABC) and GC B-cell (GCB). ABC DLBCLs exhibit genetic alterations in NF-kB modifiers and proximal components of the B-cell receptor (BCR) pathway and perturbed terminal B-cell differentiation. GCB DLBCLs have reported alterations in chromatin-modifying enzymes, PI3K signaling and Gα-migration pathway components and frequent translocations of BCL2 .
Despite the recognized molecular heterogeneity in DLBCL, previously published genomic analyses have largely focused on single types of alterations - mutations, copy number alterations (CNAs) or structural variants (SVs) - in smaller data sets with more limited clinical annotation. An unbiased comprehensive analysis of all three alteration types is needed to define discrete, clinically annotated subtypes of DLBCL.
We performed whole exome sequencing (WES) of 304 newly diagnosed DLBCLs, using an expanded bait set that captures recurrent SVs; 85% of study patients were uniformly treated with R-CHOP and had long-term follow-up. Somatic alterations (mutations, CNAs and SVs) and their clonality were determined with analytical pipelines developed at the Broad Institute. Notably, half of our DLBCL cohort lacked patient-matched normal samples, prompting the successful development of new methods to analyze tumor-only WES data. Significantly mutated genes (SMGs) were identified with MutSig2CV andrecurrent CNAs were defined with GISTIC2.0 .
With increased sample size and improved methodology, we identified 158 SMGs, CNAs and SVs; the 98 SMGs included ones previously unreported in DLBCL but described in other lymphoid malignancies or cancer. Additional insights into the putative biological function of newly identified alterations were obtained by overlaying the predicted protein changes onto their 3-dimensional protein structures.
We analyzed the mutational signatures in these DLBCLs and found that the majority of exome mutations were caused by spontaneous deamination at CpGs, a clock-like genetic signature associated with aging; only a minority of mutations were attributed to activation-induced cytidine deaminase (AID), an enzyme required for physiologic immunoglobulin receptor editing and aberrant somatic hypermutation.
IGH, BCL2, BCL6 and MYC were the most frequently rearranged genes (40%, 21%, 19% and 8%, respectively). There were 18 arm-level and 18 focal regions of copy gain and 2 arm-level and 32 focal regions of copy loss with frequencies ranging between 5-32%.
SMGs were significantly more likely to reside within focal CNAs (p=1x10-44), suggesting that these driver genes were perturbed by multiple mechanisms. Individual DLBCLs had a median of 17 genetic drivers, highlighting the need for a more comprehensive analysis. Therefore, we applied an integrated clustering approach to the recurrent mutations, CNAs and SVs and delineated 5 genetically distinct DLBCL subtypes and determined the likely temporal order of alterations within each cluster.
This unbiased approach identified a previously unappreciated favorable risk ABC subset with genetic features of an extrafollicular, possibly marginal zone origin; a more tightly defined poor risk group of ABC DLBCLs with frequent BCL2 gain and concordant MYD88L265P / CD79B mutations; a distinct poor risk subset of GCB tumors with BCL2 SVs and alterations of PTEN and epigenetic enzymes and a discrete group of good risk GCB DLBCLs with specific alterations in BCR/PI3K, JAK/STAT and BRAF pathway components and multiple histones; and a Cell-of-Origin-independent subset with biallelic inactivation of TP53, 9p21.3/CDKN2A and associated genomic instability. These findings likely explain the variability in outcome predictions with the binary ABC- vs. GCB-DLBCL transcriptional classification and the challenges of therapeutically targeting less well defined DLBCLs.
The genetically distinct DLBCL subsets provide a framework for assessing previously unrecognized heterogeneity in this disease, characterizing combinations of genetic alterations that drive DLBCL biology and guiding the development of rational single-agent and combination therapies in patients with the greatest need.
Cerhan:Janssen: Other: Scientific Advisory Board (REMICADELYM4001); Janssen: Other: Multiple Myeloma Registry Steering. Rodig:Bristol-Myers Squibb: Honoraria, Research Funding. Neuberg:Synta Pharmaceuticals: Other: Stock shares. Shipp:Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Other: Scientific Advisory Board; Cell Signaling: Honoraria; Bayer: Research Funding; Takeda: Other: Scientific Advisory Board; Merck: Other: Scientific Advisory Board; AstraZeneca: Honoraria.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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