A novel antibiotic class targeting the lipopolysaccharide transporter.

Carbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as a major global pathogen with limited treatment options1. No new antibiotic chemical class with activity against A. baumannii has reached patients in over 50 years1. Here we report the identification and optimization of tethered macrocyclic peptide (MCP) antibiotics with potent antibacterial activity against CRAB. The mechanism of action of this molecule class involves blocking the transport of bacterial lipopolysaccharide from the inner membrane to its destination on the outer membrane, through inhibition of the LptB2FGC complex. A clinical candidate derived from the MCP class, zosurabalpin (RG6006), effectively treats highly drug-resistant contemporary isolates of CRAB both in vitro and in mouse models of infection, overcoming existing antibiotic resistance mechanisms. This chemical class represents a promising treatment paradigm for patients with invasive infections due to CRAB, for whom current treatment options are inadequate, and additionally identifies LptB2FGC as a tractable target for antimicrobial drug development.

How do cyclic antibiotics with activity against Gram-negative bacteria permeate membranes? A machine learning informed experimental study.

All antibiotics have to engage bacterial amphiphilic barriers such as the lipopolysaccharide-rich outer membrane or the phospholipid-based inner membrane in some manner, either by disrupting them outright and/or permeating them and thereby allow the antibiotic to get into bacteria. There is a growing class of cyclic antibiotics, many of which are of bacterial origin, that exhibit activity against Gram-negative bacteria, which constitute an urgent problem in human health. We examine a diverse collection of these cyclic antibiotics, both natural and synthetic, which include bactenecin, polymyxin B, octapeptin, capreomycin, and Kirshenbaum peptoids, in order to identify what they have in common when they interact with bacterial lipid membranes. We find that they virtually all have the ability to induce negative Gaussian curvature (NGC) in bacterial membranes, the type of curvature geometrically required for permeation mechanisms such as pore formation, blebbing, and budding. This is interesting since permeation of membranes is a function usually ascribed to antimicrobial peptides (AMPs) from innate immunity. As prototypical test cases of cyclic antibiotics, we analyzed amino acid sequences of bactenecin, polymyxin B, and capreomycin using our recently developed machine-learning classifier trained on α-helical AMP sequences. Although the original classifier was not trained on cyclic antibiotics, a modified classifier approach correctly predicted that bactenecin and polymyxin B have the ability to induce NGC in membranes, while capreomycin does not. Moreover, the classifier was able to recapitulate empirical structure-activity relationships from alanine scans in polymyxin B surprisingly well. These results suggest that there exists some common ground in the sequence design of hybrid cyclic antibiotics and linear AMPs.

Machine learning-powered antibiotics phenotypic drug discovery.

Identification of novel antibiotics remains a major challenge for drug discovery. The present study explores use of phenotypic readouts beyond classical antibacterial growth inhibition adopting a combined multiparametric high content screening and genomic approach. Deployment of the semi-automated bacterial phenotypic fingerprint (BPF) profiling platform in conjunction with a machine learning-powered dataset analysis, effectively allowed us to narrow down, compare and predict compound mode of action (MoA). The method identifies weak antibacterial hits allowing full exploitation of low potency hits frequently discovered by routine antibacterial screening. We demonstrate that BPF classification tool can be successfully used to guide chemical structure activity relationship optimization, enabling antibiotic development and that this approach can be fruitfully applied across species. The BPF classification tool could be potentially applied in primary screening, effectively enabling identification of novel antibacterial compound hits and differentiating their MoA, hence widening the known antibacterial chemical space of existing pharmaceutical compound libraries. More generally, beyond the specific objective of the present work, the proposed approach could be profitably applied to a broader range of diseases amenable to phenotypic drug discovery.

White-to-brown metabolic conversion of human adipocytes by JAK inhibition.

The rising incidence of obesity and related disorders such as diabetes and heart disease has focused considerable attention on the discovery of new therapeutics. One promising approach has been to increase the number or activity of brown-like adipocytes in white adipose depots, as this has been shown to prevent diet-induced obesity and reduce the incidence and severity of type 2 diabetes. Thus, the conversion of fat-storing cells into metabolically active thermogenic cells has become an appealing therapeutic strategy to combat obesity. Here, we report a screening platform for the identification of small molecules capable of promoting a white-to-brown metabolic conversion in human adipocytes. We identified two inhibitors of Janus kinase (JAK) activity with no precedent in adipose tissue biology that stably confer brown-like metabolic activity to white adipocytes. Importantly, these metabolically converted adipocytes exhibit elevated UCP1 expression and increased mitochondrial activity. We further found that repression of interferon signalling and activation of hedgehog signalling in JAK-inactivated adipocytes contributes to the metabolic conversion observed in these cells. Our findings highlight a previously unknown role for the JAK-STAT pathway in the control of adipocyte function and establish a platform to identify compounds for the treatment of obesity.

THP-1 Macrophages and SGBS Adipocytes - A New Human in vitro Model System of Inflamed Adipose Tissue.

Obesity is associated with an accumulation of macrophages in adipose tissue. This inflammation of adipose tissue is a key event in the pathogenesis of several obesity-related disorders, particularly insulin resistance. Here, we summarized existing model systems that mimic the situation of inflamed adipose tissue in vitro, most of them being murine. Importantly, we introduce our newly established human model system which combines the THP-1 monocytic cell line and the preadipocyte cell strain Simpson-Golabi-Behmel syndrome (SGBS). THP-1 cells, which originate from an acute monocytic leukemia, differentiate easily into macrophages in vitro. The human preadipocyte cell strain SGBS was recently introduced as a unique tool to study human fat cell functions. SGBS cells are characterized by a high capacity for adipogenic differentiation. SGBS adipocytes are capable of fat cell-specific metabolic functions such as insulin-stimulated glucose uptake, insulin-stimulated de novo lipogenesis and ß-adrenergic-stimulated lipolysis and they secrete typical adipokines including leptin, adiponectin, and RBP4. Applying either macrophage-conditioned medium or a direct co-culture of macrophages and fat cells, our model system can be used to distinguish between paracrine and cell-contact dependent effects. In conclusion, we propose this model as a useful tool to study adipose inflammation in vitro. It represents an inexpensive, highly reproducible human system. The methods described here can be easily extended for usage of primary human macrophages and fat cells.

11beta-Hydroxysteroid dehydrogenase 1 reductase activity is dependent on a high ratio of NADPH/NADP(+) and is stimulated by extracellular glucose.

To assess the impact of the NADPH/NADP(+) ratio and the influence of extracellular glucose on 11beta-hydroxysteroid dehydrogenase 1 (11beta-HSD1) activity, we applied microsomal preparations and intact HEK-293 cells expressing 11beta-HSD1 in the presence or absence of hexose-6-phosphate dehydrogenase (H6PDH). A NADPH/NADP(+) ratio of ten or higher was required for efficient microsomal 11beta-HSD1 reductase activity. Measurements in intact cells suggested that the ER-luminal NADPH concentration is highly sensitive to fluctuating extracellular glucose levels. Lowering glucose in the culture medium dose-dependently decreased 11beta-HSD1 reductase activity and diminished the cortisol/cortisone ratio measured after 24h of incubation. Coexpression with H6PDH potentiated 11beta-HSD1 reductase activity at high glucose. This effect was significantly decreased at low glucose, with concomitantly increased 11beta-HSD1 dehydrogenase activity. In contrast, 11beta-HSD1 reductase activity in H4IIE liver cells and in 3T3-L1 adipocytes was less sensitive to changes in the medium. 11beta-HSD1 dehydrogenase activity was observed in H4IIE cells only at subphysiological glucose levels, indicating a highly efficient supply of substrate for H6PDH and NADPH generation in the ER-lumen. Our results suggest significant cell type-specific differences in ER-luminal NADPH generation that might allow a fine-tuned regulation of glucocorticoid action.