Lessons from assembling a microbial natural product and pre-fractionated extract library in an academic laboratory.

Microbial natural products are specialized metabolites that are sources of many bioactive compounds including antibiotics, antifungals, antiparasitics, anticancer agents, and probes of biology. The assembly of libraries of producers of natural products has traditionally been the province of the pharmaceutical industry. This sector has gathered significant historical collections of bacteria and fungi to identify new drug leads with outstanding outcomes-upwards of 60% of drug scaffolds originate from such libraries. Despite this success, the repeated rediscovery of known compounds and the resultant diminishing chemical novelty contributed to a pivot from this source of bioactive compounds toward more tractable synthetic compounds in the drug industry. The advent of advanced mass spectrometry tools, along with rapid whole genome sequencing and in silico identification of biosynthetic gene clusters that encode the machinery necessary for the synthesis of specialized metabolites, offers the opportunity to revisit microbial natural product libraries with renewed vigor. Assembling a suitable library of microbes and extracts for screening requires the investment of resources and the development of methods that have customarily been the proprietary purview of large pharmaceutical companies. Here, we report a perspective on our efforts to assemble a library of natural product-producing microbes and the establishment of methods to extract and fractionate bioactive compounds using resources available to most academic labs. We validate the library and approach through a series of screens for antimicrobial and cytotoxic agents. This work serves as a blueprint for establishing libraries of microbial natural product producers and bioactive extract fractions suitable for screens of bioactive compounds. ONE-SENTENCE SUMMARY: Natural products are key to discovery of novel antimicrobial agents: Here, we describe our experience and lessons learned in constructing a microbial natural product and pre-fractionated extract library.

Remote sensing and model analysis of biomass burning smoke transported across the Atlantic during the 2020 Western US wildfire season.

Biomass burning is the main source of air pollution in several regions worldwide nowadays. This predominance is expected to increase in the upcoming years as a result of the rising number of devastating wildfires due to climate change. Harmful pollutants contained in the smoke emitted by fires can alter downwind air quality both locally and remotely as a consequence of the recurrent transport of biomass burning plumes across thousands of kilometers. Here, we demonstrate how observations of carbon monoxide and aerosol optical depth retrieved from polar orbiting and geostationary meteorological satellites can be used to study the long-range transport and evolution of smoke plumes. This is illustrated through the megafire events that occurred during summer 2020 in the Western United States and the transport of the emitted smoke across the Atlantic Ocean to Europe. Analyses from the Copernicus Atmosphere Monitoring Service, which combine satellite observations with an atmospheric model, are used for comparison across the region of study and along simulated air parcel trajectories. Lidar observation from spaceborne and ground-based instruments are used to verify consistency of passive observations. Results show the potential of joint satellite-model analysis to understand the emission, transport, and processing of smoke across the world.

IASI-Derived Sea Surface Temperature Data Set for Climate Studies.

Sea surface temperature (SST) is an essential climate variable, that is directly used in climate monitoring. Although satellite measurements can offer continuous global coverage, obtaining a long-term homogeneous satellite-derived SST data set suitable for climate studies based on a single instrument is still a challenge. In this work, we assess a homogeneous SST data set derived from reprocessed Infrared Atmospheric Sounding Interferometer (IASI) level-1 (L1C) radiance data. The SST is computed using Planck's Law and simple atmospheric corrections. We assess the data set using the ERA5 reanalysis and the EUMETSAT-released IASI level-2 SST product. Over the entire period, the reprocessed IASI SST shows a mean global difference with ERA5 close to zero, a mean absolute bias under 0.5°C, with a SD of difference around 0.3°C and a correlation coefficient over 0.99. In addition, the reprocessed data set shows a stable bias and SD, which is an advantage for climate studies. The interannual variability and trends were compared with other SST data sets: ERA5, Hadley Centre's SST (HadISST), and NOAA's Optimal Interpolation SST Analysis (OISSTv2). We found that the reprocessed SST data set is able to capture the patterns of interannual variability well, showing the same areas of high interannual variability (>1.5°C), including over the tropical Pacific in January corresponding to the El Niño Southern Oscillation. Although the period studied is relatively short, we demonstrate that the IASI data set reproduces the same trend patterns found in the other data sets (i.e., cooling trend in the North Atlantic, warming trend over the Mediterranean).

Treatment with the MAO-A inhibitor clorgyline elevates monoamine neurotransmitter levels and improves affective phenotypes in a mouse model of Huntington disease.

Abnormal monoamine oxidase A and B (MAO-A/B) activity and an imbalance in monoamine neurotransmitters have been suggested to underlie the pathobiology of depression, a major psychiatric symptom observed in patients with neurodegenerative diseases, such as Huntington disease (HD). Increased MAO-A/B activity has been observed in brain tissue from patients with HD and in human and rodent HD neural cells. Using the YAC128 mouse model of HD, we studied the effect of an irreversible MAO-A inhibitor, clorgyline, on the levels of select monoamine neurotransmitters associated with affective function. We observed a decrease in striatal levels of the MAO-A/B substrates, dopamine and norepinephrine, in YAC128 HD mice compared with wild-type mice, which was accompanied by increased anxiety- and depressive-like behaviour at five months of age. Treatment for 26 days with clorgyline restored dopamine, serotonin, and norepinephrine neurotransmitter levels in the striatum and reduced anxiety- and depressive-like behaviour in YAC128 HD mice. This study supports a potential therapeutic use for MAO-A inhibitors in the treatment of depression and anxiety in patients with HD.

Effect of aspirin on bone healing in a rabbit ulnar osteotomy model.

BACKGROUND: Aspirin is frequently prescribed following orthopaedic surgery. Although there is substantial evidence that some nonsteroidal anti-inflammatory drugs (NSAIDs) are associated with delayed bone healing, there have been few studies of the effects of aspirin on bone healing and, to our knowledge, none on the effects of physiologic dosages. METHODS: Following ulnar osteotomy, fifty-six rabbits were administered a placebo (nine rabbits), indomethacin (nine rabbits given 12.5 mg/kg daily), or aspirin at various doses and schedules (2.7 mg/kg daily for ten rabbits, 10 mg/kg daily for nine rabbits, 50 mg/kg twice daily for ten rabbits, and 100 mg/kg three times daily for nine rabbits). The aspirin doses were chosen to span the clinical dosing range. The indomethacin group served as a positive control and as a relative comparison with the effect of aspirin. Radiographs were obtained every two weeks and the animals were killed at eight weeks. Mechanical testing was performed on all rabbits except for six selected for histological evaluation. RESULTS: Aspirin delayed bone healing, as demonstrated radiographically and with mechanical testing, in a dose-dependent fashion at salicylate levels equivalent to those resulting from typical human dosing (low-dose aspirin). Receiver operating characteristic analysis demonstrated a plasma salicylate threshold above 20.7 µg/mL predicting delayed bone healing. This approximates a single human dose of 325 mg. Salicylate levels above this threshold were associated with delayed bone healing similar to that caused by indomethacin. Aspirin dosing frequency did not affect bone healing. Mechanical testing was highly predictive of radiographic healing. The interobserver reliability of radiographic assessment of healing at six and eight weeks (kappa = 0.83 and 0.79, respectively) compared favorably with interobserver reliability in previous studies assessing cortical bridging. CONCLUSIONS: In a rabbit ulnar osteotomy model, aspirin delayed bone healing with a threshold equivalent to a human dose of 325 mg.

Identifying the correlation between drug/stabilizer properties and critical quality attributes (CQAs) of nanosuspension formulation prepared by wet media milling technology.

Wet media milling by top down method has proved to be an effective method to prepare nanosuspension of poorly soluble drugs/APIs. Few or no attempts have been made so far to understand the feasibility of nanosuspension formulation in terms of the mechanism of stabilization as a function of drug properties. The objective of this study was to understand the effect of drug substance and stabilizer properties to form a successful nanosuspension product. From this study, logP and enthalpy were concluded to have a direct correlation on the feasibility of formation of a stable nanosuspension. The most likely candidate for media milling was a drug substance with a high enthalpy and hydrophobicity which can be stabilized either electrostatically or sterically. The least likely candidate will be one that is hydrophilic and having a very low enthalpy value. Also the choice of an ideal stabilizer/surfactant was found to be influenced by the degree of hydrophobicity of the drug itself. Finally the morphology of the starting drug was found to significantly affect the milling time required to produce submicron particles.