Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Recombinant BCG expressing LTAK63 adjuvant induces superior protection against Mycobacterium tuberculosis

International audienceIn order to develop an improved BCG vaccine against tuberculosis we have taken advantage of the adjuvant properties of a non-toxic derivative of Escherichia coli heat labile enterotoxin (LT), LTAK63. We have constructed rBCG strains expressing LTAK63 at different expression levels. Mice immunized with BCG expressing low levels of LTAK63 (rBCG-LTAK63lo) showed higher Th1 cytokines and IL-17 in the lungs, and when challenged intratracheally with Mycobacterium tuberculosis displayed a 2.0-3.0 log reduction in CFU as compared to wild type BCG. Histopathological analysis of lung tissues from protected mice revealed a reduced inflammatory response. Immunization with rBCG-LTAK63lo also protected against a 100-fold higher challenge dose. Mice immunized with rBCG-LTAK63lo produced an increase in TGF-β as compared with BCG after challenge, with a corresponding reduction in Th1 and Th17 cytokines, as determined by Real Time RT-PCR. Furthermore, rBCG-LTAK63lo also displays protection against challenge with a highly virulent Beijing isolate. Our findings suggest that BCG with low-level expression of the LTAK63 adjuvant induces a stronger immune response in the lungs conferring higher levels of protection, and a novel mechanism subsequently triggers a regulatory immune response, which then limits the pathology. The rBCG-LTAK63lo strain can be the basis of an improved vaccine against tuberculosi