Protecting endangered megafauna through AI analysis of drone images in a low-connectivity setting: a case study from Namibia.

Assessing the numbers and distribution of at-risk megafauna such as the black rhino (Diceros bicornis) is key to effective conservation, yet such data are difficult to obtain. Many current monitoring technologies are invasive to the target animals and expensive. Satellite monitoring is emerging as a potential tool for very large animals (e.g., elephant) but detecting smaller species requires higher resolution imaging. Drones can deliver the required resolution and speed of monitoring, but challenges remain in delivering automated monitoring systems where internet connectivity is unreliable or absent. This study describes a model built to run on a drone to identify in situ images of megafauna. Compared with previously reported studies, this automated detection framework has a lower hardware cost and can function with a reduced internet bandwidth requirement for local network communication. It proposes the use of a Jetson Xavier NX, onboard a Parrot Anafi drone, connected to the internet throughout the flight to deliver a lightweight web-based notification system upon detection of the target species. The GPS location with the detected target species images is sent using MQ Telemetry Transport (MQTT), a lightweight messaging protocol using a publisher/subscriber architecture for IoT devices. It provides reliable message delivery when internet connection is sporadic. We used a YOLOv5l6 object detection architecture trained to identify a bounding box for one of five objects of interest in a frame of video. At an intersection over union (IoU) threshold of 0.5, our model achieved an average precision (AP) of 0.81 for black rhino (our primary target) and 0.83 for giraffe (Giraffa giraffa). The model was less successful at identifying the other smaller objects which were not our primary targets: 0.34, 0.25, and 0.42 for ostrich (Struthio camelus australis), springbok (Antidorcas marsupialis) and human respectively. We used several techniques to optimize performance and overcome the inherent challenge of small objects (animals) in the data. Although our primary focus for the development of the model was rhino, we included other species classes to emulate field conditions where many animal species are encountered, and thus reduce the false positive occurrence rate for rhino detections. To constrain model overfitting, we trained the model on a dataset with varied terrain, angle and lighting conditions and used data augmentation techniques (i.e., GANs). We used image tiling and a relatively larger (i.e., higher resolution) image input size to compensate for the difficulty faced in detecting small objects when using YOLO. In this study, we demonstrated the potential of a drone-based AI pipeline model to automate the detection of free-ranging megafauna detection in a remote setting and create alerts to a wildlife manager in a relatively poorly connected field environment.

Investigation of Janus Kinase (JAK) Inhibitors for Lung Delivery and the Importance of Aldehyde Oxidase Metabolism.

The Janus family of tyrosine kinases (JAK1, JAK2, JAK3, and TYK2) play an essential role in the receptor signaling of cytokines that have been implicated in the pathogenesis of severe asthma, and there is emerging interest in the development of small-molecule-inhaled JAK inhibitors as treatments. Here, we describe the optimization of a quinazoline series of JAK inhibitors and the results of mouse lung pharmacokinetic (PK) studies where only low concentrations of parent compound were observed. Subsequent investigations revealed that the low exposure was due to metabolism by aldehyde oxidase (AO), so we sought to identify quinazolines that were not metabolized by AO. We found that specific substituents at the quinazoline 2-position prevented AO metabolism and this was rationalized through computational docking studies in the AO binding site, but they compromised kinome selectivity. Results presented here highlight that AO metabolism is a potential issue in the lung.

Direct Automated MALDI Mass Spectrometry Analysis of Cellular Transporter Function: Inhibition of OATP2B1 Uptake by 294 Drugs.

OATP2B1, a member of the solute carrier (SLC) transporter family, is an important mechanism of substrate drug uptake in the intestine and liver and therefore a determinant of clinical pharmacokinetics and site of drug-drug interactions. Other SLC transporters have emerged as pharmacology targets. Studies of SLC transporter uptake to-date relied on radioisotope- or fluorescence-labeled reagents or low-throughput quantification of unlabeled compounds in cell lysate. In this study, we developed a cell-based MALDI MS workflow for investigation of OATP2B1 cellular uptake by optimizing the substrate, matrix, matrix-analyte ratio, and matrix application and normalization method. This workflow was automated and applied to characterize substrate transport kinetics and to test 294 top-marketed drugs for OATP2B1 inhibition and quantify inhibitory potencies necessary for extrapolation of clinical drug-drug interaction potential. Intra-assay reproducibility of this MALDI MS method was high (CV < 10%), and results agreed well (83% overlap) with previously published radioisotope assay data. Our results indicate that fast and robust MALDI MS cellular assays could emerge as a high-throughput label-free alternative for direct assessment of drug transporter function in DDIs and toxicities as well as enable drug discovery for transporters as pharmacology targets.

Clinically Relevant OATP2B1 Inhibitors in Marketed Drug Space.

OATP2B1 is an intestinal and hepatic drug uptake transporter. Intestinal OATP2B1 has been elucidated as the mechanism of unexpected clinical drug-drug interactions (DDIs), where drug exposure was unexpectedly decreased with unchanged half-life. Hepatic OATP2B1 may be an understudied clinical DDI mechanism. The aim of the present work was to understand the prevalence of clinically relevant intestinal and hepatic OATP2B1 inhibitors in marketed drug space. HEK293 cells stably overexpressing human OATP2B1 or vector control were generated and cultured for 72 h in a 96-well format. OATP2B1-mediated uptake of dibromofluorescein (DBF) was found to be optimal at 10 µM concentration and 30 min incubation time. A total of 294 drugs (top 300 marketed drugs, excluding biologics and restricted drugs, supplemented with ∼100 small-molecule drugs) were screened for OATP2B1 inhibition at 10 µM. Drugs demonstrating ≥50% inhibition in this screen were advanced for IC50 determination, which was extrapolated to clinical intestinal and hepatic OATP2B1 inhibition as per 2017 FDA DDI guidance. Of the 294 drugs screened, 67 elicited ≥50% inhibition of OATP2B1-mediated DBF uptake at 10 µM screening concentration. For the 67 drugs flagged in the single-concentration inhibition screen, upon evaluation of a full concentration range, IC50 values could be determined for 58 drugs. OATP2B1 IC50 values established for these 58 drugs were extrapolated as potentially clinically relevant at the intestinal level for 38 orally administered drugs (Igut/IC50 ≥ 10), and 17 were flagged as potential clinical inhibitors of hepatic OATP2B1 uptake (1 + Iin,max,u/IC50 ≥ 1.1). This analysis of 294 drugs demonstrated prevalence of clinically relevant intestinal and hepatic OATP2B1 inhibitors to be 13 and 6%, respectively. As OATP2B1-inhibitor drugs are not exceedingly rare, these results suggest that clinical OATP2B1 DDIs have been rarely observed because OATP2B1 is uncommonly the predominant determinant of drug disposition.

Optimization of Orally Bioavailable PI3Kδ Inhibitors and Identification of Vps34 as a Key Selectivity Target.

Optimization of a lead series of PI3Kδ inhibitors based on a dihydroisobenzofuran core led to the identification of potent, orally bioavailable compound 19. Selectivity profiling of compound 19 showed similar potency for class III PI3K, Vps34, and PI3Kδ, and compound 19 was not well-tolerated in a 7-day rat toxicity study. Structure-based design led to an improvement in selectivity for PI3Kδ over Vps34 and, a focus on oral phramacokinetics properties resulted in the discovery of compound 41, which showed improved toxicological outcomes at similar exposure levels to compound 19.

Chemical proteomics reveals target selectivity of clinical Jak inhibitors in human primary cells.

Kinobeads are a set of promiscuous kinase inhibitors immobilized on sepharose beads for the comprehensive enrichment of endogenously expressed protein kinases from cell lines and tissues. These beads enable chemoproteomics profiling of kinase inhibitors of interest in dose-dependent competition studies in combination with quantitative mass spectrometry. We present improved bead matrices that capture more than 350 protein kinases and 15 lipid kinases from human cell lysates, respectively. A multiplexing strategy is suggested that enables determination of apparent dissociation constants in a single mass spectrometry experiment. Miniaturization of the procedure enabled determining the target selectivity of the clinical BCR-ABL inhibitor dasatinib in peripheral blood mononuclear cell (PBMC) lysates from individual donors. Profiling of a set of Jak kinase inhibitors revealed kinase off-targets from nearly all kinase families underpinning the need to profile kinase inhibitors against the kinome. Potently bound off-targets of clinical inhibitors suggest polypharmacology, e.g. through MRCK alpha and beta, which bind to decernotinib with nanomolar affinity.

Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response.

Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resolution of aerial imagery is an order of magnitude higher than the imagery produced by the most sophisticated commercial satellites today. Both the United States Federal Emergency Management Agency (FEMA) and the European Commission's Joint Research Center (JRC) have noted that aerial imagery will inevitably present a big data challenge. The purpose of this article is to get ahead of this future challenge by proposing a hybrid crowdsourcing and real-time machine learning solution to rapidly process large volumes of aerial data for disaster response in a time-sensitive manner. Crowdsourcing can be used to annotate features of interest in aerial images (such as damaged shelters and roads blocked by debris). These human-annotated features can then be used to train a supervised machine learning system to learn to recognize such features in new unseen images. In this article, we describe how this hybrid solution for image analysis can be implemented as a module (i.e., Aerial Clicker) to extend an existing platform called Artificial Intelligence for Disaster Response (AIDR), which has already been deployed to classify microblog messages during disasters using its Text Clicker module and in response to Cyclone Pam, a category 5 cyclone that devastated Vanuatu in March 2015. The hybrid solution we present can be applied to both aerial and satellite imagery and has applications beyond disaster response such as wildlife protection, human rights, and archeological exploration. As a proof of concept, we recently piloted this solution using very high-resolution aerial photographs of a wildlife reserve in Namibia to support rangers with their wildlife conservation efforts (SAVMAP project, http://lasig.epfl.ch/savmap ). The results suggest that the platform we have developed to combine crowdsourcing and machine learning to make sense of large volumes of aerial images can be used for disaster response.

Screening Pools of Compounds against Multiple Endogenously Expressed Targets in a Chemoproteomics Binding Assay.

Chemoproteomics-based competition-binding assays allow the screening of compounds against endogenous proteins in cell or tissue extracts, but these assays are hampered by low throughput and high cost. Using compound pools rather than single compounds in a screening campaign holds the promise of increased efficiency and substantial cost reduction. Previous attempts to screen compounds in pools often fell short due to complex data tracking, deconvolution issues, compound interferences, and automation problems. The desire to screen compounds in a high-throughput chemoproteomics format sparked a reassessment of compound pooling. Through the integration of acoustic dispensing, we enabled a flexible pooling process, allowing mixture creation by combining randomized or specific samples to create defined pools. Automation enabled end-to-end tracking, using barcode scan check points and output files to track data and ensure integrity during the mixture creation process. The compound pooling approach proved to be highly compatible with the chemoproteomics assay technology. Pools of 10 compounds in a single well did not show compound interference effects or increased false-positive/negative rates. In the present study, four targets, TBK1, PI3Kδ, PI3Kγ, and mTOR, were screened using a chemoproteomics approach against pools of 10 compounds per well, resulting in robust hit identification.

Thermal proteome profiling monitors ligand interactions with cellular membrane proteins.

We extended thermal proteome profiling to detect transmembrane protein-small molecule interactions in cultured human cells. When we assessed the effects of detergents on ATP-binding profiles, we observed shifts in denaturation temperature for ATP-binding transmembrane proteins. We also observed cellular thermal shifts in pervanadate-induced T cell-receptor signaling, delineating the membrane target CD45 and components of the downstream pathway, and with drugs affecting the transmembrane transporters ATP1A1 and MDR1.

Thermal proteome profiling for unbiased identification of direct and indirect drug targets using multiplexed quantitative mass spectrometry.

The direct detection of drug-protein interactions in living cells is a major challenge in drug discovery research. Recently, we introduced an approach termed thermal proteome profiling (TPP), which enables the monitoring of changes in protein thermal stability across the proteome using quantitative mass spectrometry. We determined the intracellular thermal profiles for up to 7,000 proteins, and by comparing profiles derived from cultured mammalian cells in the presence or absence of a drug we showed that it was possible to identify direct and indirect targets of drugs in living cells in an unbiased manner. Here we demonstrate the complete workflow using the histone deacetylase inhibitor panobinostat. The key to this approach is the use of isobaric tandem mass tag 10-plex (TMT10) reagents to label digested protein samples corresponding to each temperature point in the melting curve so that the samples can be analyzed by multiplexed quantitative mass spectrometry. Important steps in the bioinformatic analysis include data normalization, melting curve fitting and statistical significance determination of compound concentration-dependent changes in protein stability. All analysis tools are made freely available as R and Python packages. The workflow can be completed in 2 weeks.

Tracking cancer drugs in living cells by thermal profiling of the proteome.

The thermal stability of proteins can be used to assess ligand binding in living cells. We have generalized this concept by determining the thermal profiles of more than 7000 proteins in human cells by means of mass spectrometry. Monitoring the effects of small-molecule ligands on the profiles delineated more than 50 targets for the kinase inhibitor staurosporine. We identified the heme biosynthesis enzyme ferrochelatase as a target of kinase inhibitors and suggest that its inhibition causes the phototoxicity observed with vemurafenib and alectinib. Thermal shifts were also observed for downstream effectors of drug treatment. In live cells, dasatinib induced shifts in BCR-ABL pathway proteins, including CRK/CRKL. Thermal proteome profiling provides an unbiased measure of drug-target engagement and facilitates identification of markers for drug efficacy and toxicity.

Life history analysis of integrative and conjugative element activation in growing microcolonies of Pseudomonas.

Integrative and conjugative elements (ICE) are in some ways parasitic mobile DNA that propagate vertically through replication with the bacterial host chromosome but at low frequencies can excise and invade new recipient cells through conjugation and reintegration (horizontal propagation). The factors that contribute to successful horizontal propagation are not very well understood. Here, we study the influence of host cell life history on the initiation of transfer of a model ICE named ICEclc in bacteria of the genus Pseudomonas. We use time-lapse microscopy of growing and stationary-phase microcolonies of ICEclc bearing cells in combination with physiological staining and gene reporter analysis in stationary-phase suspended cells. We provide evidence that cell age and cell lineage are unlikely to play a role in the decision to initiate the ICEclc transfer program. In contrast, cells activating ICEclc show more often increased levels of reactive oxygen species and membrane damage than nonactivating cells, suggesting that some form of biochemical damage may make cells more prone to ICEclc induction. Finally, we find that ICEclc active cells appear spatially at random in a microcolony, which may have been a selective advantage for maximizing ICEclc horizontal transmission to new recipient species.

Improved statistical analysis of low abundance phenomena in bimodal bacterial populations.

Accurate detection of subpopulation size determinations in bimodal populations remains problematic yet it represents a powerful way by which cellular heterogeneity under different environmental conditions can be compared. So far, most studies have relied on qualitative descriptions of population distribution patterns, on population-independent descriptors, or on arbitrary placement of thresholds distinguishing biological ON from OFF states. We found that all these methods fall short of accurately describing small population sizes in bimodal populations. Here we propose a simple, statistics-based method for the analysis of small subpopulation sizes for use in the free software environment R and test this method on real as well as simulated data. Four so-called population splitting methods were designed with different algorithms that can estimate subpopulation sizes from bimodal populations. All four methods proved more precise than previously used methods when analyzing subpopulation sizes of transfer competent cells arising in populations of the bacterium Pseudomonas knackmussii B13. The methods' resolving powers were further explored by bootstrapping and simulations. Two of the methods were not severely limited by the proportions of subpopulations they could estimate correctly, but the two others only allowed accurate subpopulation quantification when this amounted to less than 25% of the total population. In contrast, only one method was still sufficiently accurate with subpopulations smaller than 1% of the total population. This study proposes a number of rational approximations to quantifying small subpopulations and offers an easy-to-use protocol for their implementation in the open source statistical software environment R.

Cell differentiation to "mating bodies" induced by an integrating and conjugative element in free-living bacteria.

Lateral gene transfer (LGT) is one of the most important processes leading to prokaryotic genome innovation. LGT is typically associated with conjugative plasmids and bacteriophages, but recently, a new class of mobile DNA known as integrating and conjugative elements (ICE) was discovered, which is abundant and widespread among bacterial genomes. By studying at the single-cell level the behavior of a prevalent ICE type in the genus Pseudomonas, we uncover the remarkable way in which the ICE orchestrates host cell differentiation to ensure horizontal transmission. We find that the ICE induces a state of transfer competence (tc) in 3%-5% of cells in a population under nongrowing conditions. ICE factors control the development of tc cells into specific assemblies that we name "mating bodies." Interestingly, cells in mating bodies undergo fewer and slower division than non-tc cells and eventually lyse. Mutations in ICE genes disrupting mating-body formation lead to 5-fold decreased ICE transfer rates. Hence, by confining the tc state to a small proportion of the population, ICE horizontal transmission is achieved with little cost in terms of vertical transmission. Given the low transfer frequencies of most ICE, we anticipate regulation by subpopulation differentiation to be widespread.

Cellular variability of RpoS expression underlies subpopulation activation of an integrative and conjugative element.

Conjugative transfer of the integrative and conjugative element ICEclc in the bacterium Pseudomonas knackmussii is the consequence of a bistable decision taken in some 3% of cells in a population during stationary phase. Here we study the possible control exerted by the stationary phase sigma factor RpoS on the bistability decision. The gene for RpoS in P. knackmussii B13 was characterized, and a loss-of-function mutant was produced and complemented. We found that, in absence of RpoS, ICEclc transfer rates and activation of two key ICEclc promoters (P(int) and P(inR)) decrease significantly in cells during stationary phase. Microarray and gene reporter analysis indicated that the most direct effect of RpoS is on P(inR), whereas one of the gene products from the P(inR)-controlled operon (InrR) transmits activation to P(int) and other ICEclc core genes. Addition of a second rpoS copy under control of its native promoter resulted in an increase of the proportion of cells expressing the P(int) and P(inR) promoters to 18%. Strains in which rpoS was replaced by an rpoS-mcherry fusion showed high mCherry fluorescence of individual cells that had activated P(int) and P(inR), whereas a double-copy rpoS-mcherry-containing strain displayed twice as much mCherry fluorescence. This suggested that high RpoS levels are a prerequisite for an individual cell to activate P(inR) and thus ICEclc transfer. Double promoter-reporter fusions confirmed that expression of P(inR) is dominated by extrinsic noise, such as being the result of cellular variability in RpoS. In contrast, expression from P(int) is dominated by intrinsic noise, indicating it is specific to the ICEclc transmission cascade. Our results demonstrate how stochastic noise levels of global transcription factors can be transduced to a precise signaling cascade in a subpopulation of cells leading to ICE activation.

A selective inhibitor reveals PI3Kγ dependence of T(H)17 cell differentiation.

We devised a high-throughput chemoproteomics method that enabled multiplexed screening of 16,000 compounds against native protein and lipid kinases in cell extracts. Optimization of one chemical series resulted in CZC24832, which is to our knowledge the first selective inhibitor of phosphoinositide 3-kinase γ (PI3Kγ) with efficacy in in vitro and in vivo models of inflammation. Extensive target- and cell-based profiling of CZC24832 revealed regulation of interleukin-17-producing T helper cell (T(H)17) differentiation by PI3Kγ, thus reinforcing selective inhibition of PI3Kγ as a potential treatment for inflammatory and autoimmune diseases.

Working with small molecules: preparing and storing stock solutions and determination of kinetic solubility.

The handling of organic compounds in the laboratory requires the use of organic (co-) solvents to mediate solubility. Advantages and disadvantages of the widely used solvent dimethylsulfoxide (DMSO) are discussed, and guidelines for dissolution and storage of compounds are given. Finally, nephelometry is introduced as a fast method to determine the kinetic solubility of a compound.

Stochasticity and bistability in horizontal transfer control of a genomic island in Pseudomonas.

Genomic islands (GEI) comprise a recently recognized large family of potentially mobile DNA elements and play an important role in the rapid differentiation and adaptation of bacteria. Most importantly, GEIs have been implicated in the acquisition of virulence factors, antibiotic resistances or toxic compound metabolism. Despite detailed information on coding capacities of GEIs, little is known about the regulatory decisions in individual cells controlling GEI transfer. Here, we show how self-transfer of ICEclc, a GEI in Pseudomonas knackmussii B13 is controlled by a series of stochastic processes, the result of which is that only a few percent of cells in a population will excise ICEclc and launch transfer. Stochastic processes have been implicated before in producing bistable phenotypic transitions, such as sporulation and competence development, but never before in horizontal gene transfer (HGT). Bistability is instigated during stationary phase at the level of expression of an activator protein InrR that lays encoded on ICEclc, and then faithfully propagated to a bistable expression of the IntB13 integrase, the enzyme responsible for excision and integration of the ICEclc. Our results demonstrate how GEI of a very widespread family are likely to control their transfer rates. Furthermore, they help to explain why HGT is typically confined to few members within a population of cells. The finding that, despite apparent stochasticity, HGT rates can be modulated by external environmental conditions provides an explanation as to why selective conditions can promote DNA exchange.

A novel epsilon-cleavage within the transmembrane domain of the Alzheimer amyloid precursor protein demonstrates homology with Notch processing.

Proteolytic processing of the transmembrane domain of the amyloid precursor protein (APP) is a key component of Alzheimer's disease pathogenesis. Using C-terminally tagged APP derivatives, we have identified by amino-terminal sequencing a novel cleavage site of APP, at Leu-49, distal to the gamma-secretase site. This was termed -cleavage. Brefeldin A treatment and pulse-chase experiments indicate that this cleavage occurs late in the secretory pathway. The level of -cleavage is decreased by expression of presenilin-1 mutants known to impair Abeta formation, and it is sensitive to the gamma-secretase inhibitors MDL28170 and L-685,458. Remarkably, it shares similarities with site 3 cleavage of Notch-1: membrane topology, cleavage before a valine, dependence on presenilins, and inhibition profile.