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Anaerobic gut fungi in the phylum Neocallimastigomycota typically inhabit the digestive tracts of large mammalian herbivores, where they play an integral role in the decomposition of raw lignocellulose into its constitutive sugar monomers. However, quantitative tools to study their physiology are lacking, partially due to their complex and unresolved metabolism that includes the largely uncharacterized fungal hydrogenosome. Modern omics approaches combined with metabolic modeling can be used to establish an understanding of gut fungal metabolism and develop targeted engineering strategies to harness their degradation capabilities for lignocellulosic bioprocessing. Here, we introduce a high-quality genome of the anaerobic fungus Neocallimastix lanati from which we constructed the first genome-scale metabolic model of an anaerobic fungus. Relative to its size (200 Mbp, sequenced at 62× depth), it is the least fragmented publicly available gut fungal genome to date. Of the 1,788 lignocellulolytic enzymes annotated in the genome, 585 are associated with the fungal cellulosome, underscoring the powerful lignocellulolytic potential of N. lanati The genome-scale metabolic model captures the primary metabolism of N. lanati and accurately predicts experimentally validated substrate utilization requirements. Additionally, metabolic flux predictions are verified by 13C metabolic flux analysis, demonstrating that the model faithfully describes the underlying fungal metabolism. Furthermore, the model clarifies key aspects of the hydrogenosomal metabolism and can be used as a platform to quantitatively study these biotechnologically important yet poorly understood early-branching fungi.IMPORTANCE Recent genomic analyses have revealed that anaerobic gut fungi possess both the largest number and highest diversity of lignocellulolytic enzymes of all sequenced fungi, explaining their ability to decompose lignocellulosic substrates, e.g., agricultural waste, into fermentable sugars. Despite their potential, the development of engineering methods for these organisms has been slow due to their complex life cycle, understudied metabolism, and challenging anaerobic culture requirements. Currently, there is no framework that can be used to combine multi-omic data sets to understand their physiology. Here, we introduce a high-quality PacBio-sequenced genome of the anaerobic gut fungus Neocallimastix lanati Beyond identifying a trove of lignocellulolytic enzymes, we use this genome to construct the first genome-scale metabolic model of an anaerobic gut fungus. The model is experimentally validated and sheds light on unresolved metabolic features common to gut fungi. Model-guided analysis will pave the way for deepening our understanding of anaerobic gut fungi and provides a systematic framework to guide strain engineering efforts of these organisms for biotechnological use.

Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production. We also include practical advice for the practitioner in terms of data management, algorithm libraries, computational resources, and important non-technical issues. A variety of applications ranging from pathway construction and optimization, to genetic editing optimization, cell factory testing, and production scale-up are discussed. Moreover, the promising relationship between machine learning and mechanistic models is thoroughly reviewed. Finally, the future perspectives and most promising directions for this combination of disciplines are examined.

Despite broad scientific interest in harnessing the power of Earth's microbiomes, knowledge gaps hinder their efficient use for addressing urgent societal and environmental challenges. We argue that structuring research and technology developments around a design-build-test-learn (DBTL) cycle will advance microbiome engineering and spur new discoveries of the basic scientific principles governing microbiome function. In this Review, we present key elements of an iterative DBTL cycle for microbiome engineering, focusing on generalizable approaches, including top-down and bottom-up design processes, synthetic and self-assembled construction methods, and emerging tools to analyse microbiome function. These approaches can be used to harness microbiomes for broad applications related to medicine, agriculture, energy and the environment. We also discuss key challenges and opportunities of each approach and synthesize them into best practice guidelines for engineering microbiomes. We anticipate that adoption of a DBTL framework will rapidly advance microbiome-based biotechnologies aimed at improving human and animal health, agriculture and enabling the bioeconomy.

Stephen Dale, Shift Change: Scenes from a Post-industrial Revolution (Toronto: Between the Lines, 2021) EVEN BEFORE BEING hit by the biggest pandemic in a century, cities across Canada and the [...]

Microbial communities mediating anaerobic ammonium oxidation (anammox) represent one of the most energy-efficient environmental biotechnologies for nitrogen removal from wastewater. However, little is known about the functional role heterotrophic bacteria play in anammox granules. Here, we use genome-centric metagenomics to recover 17 draft genomes of anammox and heterotrophic bacteria from a laboratory-scale anammox bioreactor. We combine metabolic network reconstruction with metatranscriptomics to examine the gene expression of anammox and heterotrophic bacteria and to identify their potential interactions. We find that Chlorobi-affiliated bacteria may be highly active protein degraders, catabolizing extracellular peptides while recycling nitrate to nitrite. Other heterotrophs may also contribute to scavenging of detritus and peptides produced by anammox bacteria, and potentially use alternative electron donors, such as H2, acetate and formate. Our findings improve the understanding of metabolic activities and interactions between anammox and heterotrophic bacteria and offer the first transcriptional insights on ecosystem function in anammox granules.

The inhibitory-kappaB kinases (IKKs) IKKα and IKKβ play central roles in regulating the non-canonical and canonical NF-κB signalling pathways. Whilst the proteins that transduce the signals of each pathway have been extensively characterised, the clear dissection of the functional roles of IKKα-mediated non-canonical NF-κB signalling versus IKKβ-driven canonical signalling remains to be fully elucidated. Progress has relied upon complementary molecular and pharmacological tools; however, the lack of highly potent and selective IKKα inhibitors has limited advances. Herein, we report the development of an aminoindazole-pyrrolo[2,3-b]pyridine scaffold into a novel series of IKKα inhibitors. We demonstrate high potency and selectivity against IKKα over IKKβ in vitro and explain the structure–activity relationships using structure-based molecular modelling. We show selective target engagement with IKKα in the non-canonical NF-κB pathway for both U2OS osteosarcoma and PC-3M prostate cancer cells by employing isoform-related pharmacodynamic markers from both pathways. Two compounds (SU1261 [IKKα Ki = 10 nM; IKKβ Ki = 680 nM] and SU1349 [IKKα Ki = 16 nM; IKKβ Ki = 3352 nM]) represent the first selective and potent pharmacological tools that can be used to interrogate the different signalling functions of IKKα and IKKβ in cells. Our understanding of the regulatory role of IKKα in various inflammatory-based conditions will be advanced using these pharmacological agents. [ABSTRACT FROM AUTHOR]

For decades, superfluid helium has attracted the interest of the scientific community as an extremely pure realisation of a quantum liquid, only accessible at temperatures close to absolute zero. Previously, helium films have only been observed directly using X-rays. However, this method is limited to temperatures above 1 K due to the high levels of energy deposition, and it also suffers from an inability to distinguish between helium isotopes. Here we show that a 3He layer on top of a phase separated mixture film at 170 mK gradually dissolves into the 4He with increasing temperature. We also observe an anomaly in film behaviour near 300 mK and unexpected restoration of the layered structure at 1.5 K which is consistent with a re-entrant phase transition leading to the suppression of superfluidity in the film near 300 mK. Our successful application of neutron scattering to study helium films at ultra-low temperatures opens up new possibilities for future research. Superfluidity, a liquid exhibiting frictionless flow, is so far limited to observations in low-temperature 3He and 4He, where the underlying mechanisms governing the quantum state are complex and different for each isotope, making for a fascinating but challenging phenomenon to study experimentally. The authors use isotope-sensitive neutron reflectometry to investigate mixed 3He/4He superfluid He films on a Si surface, and resolve the structural features and phase transitions that occur with changing temperature. [ABSTRACT FROM AUTHOR]

Sherry Lee Linkon, The Half-Life of Deindustrialization: Working Class Writing about Economic Restructuring (Ann Arbor: University of Michigan Press 2018) LIKE MANY SCHOLARS of deindustrialization and the working class in [...]