Amoebae and bacteria interact within predator-prey and host-pathogen relationships, but the general response of amoeba to bacteria is not well understood. The amoeba Dictyostelium discoideum feeds on, and is colonized by, diverse bacterial species, including Gram-positive [Gram(+)] and Gram-negative [Gram(-)] bacteria, two major groups of bacteria that differ in structure and macromolecular composition.

Bevirimat, the prototype Human Immunodeficiency Virus type 1 (HIV-1) maturation inhibitor, is highly potent in cell culture and efficacious in HIV-1 infected patients. In contrast to inhibitors that target the active site of the viral protease, bevirimat specifically inhibits a single cleavage event, the final processing step for the Gag precursor where p25 (CA-SP1) is cleaved to p24 (CA) and SP1.

The social amoebae (Dictyostelia) are a diverse group of Amoebozoa that achieve multicellularity by aggregation and undergo morphogenesis into fruiting bodies with terminally differentiated spores and stalk cells. There are four groups of dictyostelids, with the most derived being a group that contains the model species Dictyostelium discoideum.

Antiretroviral therapy has led to a profound improvement in the clinical care of HIV-infected patients. However, drug tolerability and the evolution of drug resistance have limited treatment options for many patients. Maturation inhibitors are a new class of antiretroviral agents for treatment of HIV-1. They act by interfering with the maturation of the virus by blocking the last step in Gag processing: the cleavage of the capsid-spacer peptide 1 (CA-SP1) intermediate to mature CA by the viral protease (PR). The first-in-class maturation inhibitor bevirimat (BVM) failed against a subset of HIV-1 isolates in clinical trials due to polymorphisms present in the CA-SP1 region of the Gag protein. Sequence analysis indicated that these polymorphisms are more common in non-clade B strains of HIV-1 such as HIV-1 clade C. Indeed, BVM was found to be ineffective against HIV-1 clade C molecular clones tested in this study. A number of BVM analogs were synthesized by chemical modifications at the C-28 position to improve its activity. The new BVM analogs displayed potent activity against HIV-1 clade B and C and also reduced infectivity of the virus. This study identifies novel and broadly active BVM analogs that may ultimately demonstrate efficacy in the clinic.

Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability.

γ-Glutamyl transpeptidase 1 (GGT1) is an N-glycosylated membrane protein that catabolizes extracellular glutathione and other γ-glutamyl-containing substrates. In a variety of disease states, including tumor formation, the enzyme is shed from the surface of the cell and can be detected in serum. The structures of the N-glycans on human GGT1 (hGGT1) have been shown to be tissue-specific. Tumor-specific changes in the glycans have also been observed, suggesting that the N-glycans on hGGT1 would be an important biomarker for detecting tumors and monitoring their progression during treatment. However, the large quantities of purified protein required to fully characterize the carbohydrate content poses a significant challenge for biomarker development. Herein, we investigated a new antibody-lectin sandwich array (ALSA) platform to determine whether this microanalytical technique could be applied to the characterization of N-glycan content of hGGT1 in complex biological samples.

Maturation of HIV-1 particles encompasses a complex morphological transformation of Gag via an orchestrated series of proteolytic cleavage events. A longstanding question concerns the structure of the C-terminal region of CA and the peptide SP1 (CA-SP1), which represents an intermediate during maturation of the HIV-1 virus. By integrating NMR, cryo-EM, and molecular dynamics simulations, we show that in CA-SP1 tubes assembled in vitro, which represent the features of an intermediate assembly state during maturation, the SP1 peptide exists in a dynamic helix-coil equilibrium, and that the addition of the maturation inhibitors Bevirimat and DFH-055 causes stabilization of a helical form of SP1. Moreover, the maturation-arresting SP1 mutation T8I also induces helical structure in SP1 and further global dynamical and conformational changes in CA. Overall, our results show that dynamics of CA and SP1 are critical for orderly HIV-1 maturation and that small molecules can inhibit maturation by perturbing molecular motions.

Colorectal cancers (CRCs) are prevalent worldwide, yet current treatments remain inadequate. Using chemical genetic screens, we identify that co-inhibition of topoisomerase I (TOP1) and NEDD8 is synergistically cytotoxic in human CRC cells. Combination of the TOP1 inhibitor irinotecan or its bioactive metabolite SN38 with the NEDD8-activating enzyme inhibitor pevonedistat exhibits synergy in CRC patient-derived organoids and xenografts. Mechanistically, we show that pevonedistat blocks the ubiquitin/proteasome-dependent repair of TOP1 DNA-protein crosslinks (TOP1-DPCs) induced by TOP1 inhibitors and that the CUL4-RBX1 complex (CRL4) is a prominent ubiquitin ligase acting on TOP1-DPCs for proteasomal degradation upon auto-NEDD8 modification during replication. We identify DCAF13, a DDB1 and Cullin Associated Factor, as the receptor of TOP1-DPCs for CRL4. Our study not only uncovers a replication-coupled ubiquitin-proteasome pathway for the repair of TOP1-DPCs but also provides molecular and translational rationale for combining TOP1 inhibitors and pevonedistat for CRC and other types of cancers.

Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant information about genetic networks, but mining the data is not a trivial task. Algorithms that infer Bayesian networks from expression data are powerful tools for learning complex genetic networks, since they can incorporate prior knowledge and uncover higher-order dependencies among genes. However, these algorithms are computationally demanding, so novel techniques that allow targeted exploration for discovering new members of known pathways are essential.

Evolutionarily divergent organisms often share developmental anatomies despite vast differences between their genome sequences. The social amoebae Dictyostelium discoideum and Dictyostelium purpureum have similar developmental morphologies although their genomes are as divergent as those of man and jawed fish.