A Mycobacterium avium subsp. paratuberculosis relA deletion mutant and a 35 kDa major membrane protein elicit development of cytotoxic T lymphocytes with ability to kill intracellular bacteria

Efforts to develop live attenuated vaccines against Mycobacterium avium subspecies paratuberculosis (Map), using indirect methods to screen Map deletion mutants for potential efficacy, have not been successful. A reduction in the capacity to survive in macrophages has not predicted the ability of mutants to survive in vivo. Previous studies for screening of three deletion mutants in cattle and goats revealed one mutant, with a deletion in relA (ΔMap/relA), could not establish a persistent infection. Further studies, using antigen presenting cells (APC), blood dendritic cells and monocyte derived DC, pulsed with ΔMap/relA or a 35 kDa Map membrane protein (MMP) revealed a component of the response to ΔMap/relA was directed towards MMP. As reported herein, we developed a bacterium viability assay and cell culture assays for analysis and evaluation of cytotoxic T cells generated against ΔMap/relA or MMP. Analysis of the effector activity of responding cells revealed the reason ΔMap/relA could not establish a persistent infection was that vaccination elicited development of cytotoxic CD8 T cells (CTL) with the capacity to kill intracellular bacteria. We demonstrated the same CTL response could be elicited with two rounds of antigenic stimulation of APC pulsed with ΔMap/relA or MMP ex vivo. Cytotoxicity was mediated through the perforin granzyme B pathway. Finally, cognate recognition of peptides presented in context of MHC I and II molecules to CD4 and CD8 T cells is required for development of CTL

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

In Vitro Evaluation of the Biological Responses of Canine Macrophages Challenged with PLGA Nanoparticles Containing Monophosphoryl Lipid A

Poly (lactic-co-glycolic acid) nanoparticles (PLGA NPs) have been considerably studied as a promising biodegradable delivery system to induce effective immune responses and to improve stability, safety, and cost effectiveness of vaccines. The study aimed at evaluating early inflammatory effects and cellular safety of PLGA NPs, co-encapsulating ovalbumin (PLGA/OVA NPs), as a model antigen and the adjuvant monophosphoryl lipid A (PLGA/MPLA NPs) as an adjuvant, on primary canine macrophages. The PLGA NPs constructs were prepared following the emulsion-solvent evaporation technique and further physic-chemically characterized. Peripheral blood mononuclear cells were isolated from canine whole blood by magnetic sorting and further cultured to generate macrophages. The uptake of PLGA NP constructs by macrophages was demonstrated by flow cytometry, transmission electron microscopy and confocal microscopy. Macrophage viability and morphology were evaluated by trypan blue exclusion and light microscopy. Macrophages were immunophenotyped for the expression of MHC-I and MHC-II and gene expression of Interleukin-10 (IL-10), Interleukin-12 (IL-12p40), and tumor necrosis factor alpha (TNF-α) were measured. The results showed that incubation of PLGA NP constructs with macrophages revealed effective early uptake of the PLGA NPs without altering the viability of macrophages. PLGA/OVA/MPLA NPs strongly induced TNF-α and IL-12p40 expression by macrophages as well as increase relative expression of MHC-I but not MHC-II molecules. Taken together, these results indicated that PLGA NPs with addition of MPLA represent a good model, when used as antigen carrier, for further, in vivo, work aiming to evaluate their potential to induce strong, specific, immune responses in dogs

A peptide-based vaccine for Mycobacterium avium subspecies paratuberculosis

Recent efforts to develop a live attenuated vaccine against Mycobacterium avium subsp. paratuberculosis (Map), the causative agent of Johne’s disease (JD), revealed relA is important in Map virulence. Deletion of the relA gene impairs the ability of Map to establish a persistent infection. Analysis of the basis for this observation revealed infection with a relA deletion mutant (DrelA) elicits development of cytotoxic CD8 T cells (CTL) with the ability to kill intracellular bacteria. Further analysis of the recall response elicited by DrelA vaccination showed a 35 kDa membrane peptide (MMP) is one of the targets of the immune response, suggesting it might be possible to develop a peptide-based vaccine based on MMP. To explore this possibility, ex vivo vaccination studies were conducted with MMP alone and incorporated into a nanoparticle (NP) vector comprised of poly (D, L-lactide-co-glycolide) and monophosphoryl lipid A (PLGA/MPLA). As reported, ex vivo vaccination studies showed CD8 CTL were elicited with classic and monocyte derived dendritic cells (cDC and MoDC) pulsed with MMP alone and incorporated into a PGLA/MPLA vector. Incorporation of MMP into a NP vector enhanced the ability of CD8 CTL to kill intra- cellular bacteria. The findings indicate incorporation of MMP into a PGLA/MPLA nanoparticle vector is one of the possible ways to develop a MMP based vaccine for Johne’s disease