Centrioles are key eukaryotic organelles that are responsible for the formation of cilia and flagella, and for organizing the microtubule network and the mitotic spindle in animals. Centriole assembly requires oligomerization of the essential protein spindle assembly abnormal 6 (SAS-6), which forms a structural scaffold templating the organization of further organelle components. A dimerization interaction between SAS-6 N-terminal “head” domains was previously shown to be essential for protein oligomerization in vitro and for function in centriole assembly. Here, we developed a pharmacophore model allowing us to assemble a library of low-molecular-weight ligands predicted to bind the SAS-6 head domain and inhibit protein oligomerization. We demonstrate using NMR spectroscopy that a ligand from this family binds at the head domain dimerization site of algae, nematode, and human SAS-6 variants, but also that another ligand specifically recognizes human SAS-6. Atomistic molecular dynamics simulations starting from SAS-6 head domain crystallographic structures, including that of the human head domain which we now resolve, suggest that ligand specificity derives from favorable Van der Waals interactions with a hydrophobic cavity at the dimerization site.

L. Oeding
Trans. Moscow Math. Soc. 83 (), 227-250.
Abstract, references and article information

A. Kh. Khachatryan, Kh. A. Khachatryan and A. Zh. Narimanyan
Trans. Moscow Math. Soc. 83 (), 183-200.
Abstract, references and article information

Artificial Intelligence Apps Risk Entrenching India’s Socio-economic Inequities Expert comment sysadmin 14 March 2018

Artificial intelligence applications will not be a panacea for addressing India’s grand challenges. Data bias and unequal access to technology gains will entrench existing socio-economic fissures.

Artificial intelligence (AI) is high on the Indian government’s agenda. Some days ago, Prime Minister Narendra Modi inaugurated the Wadhwani Institute for Artificial Intelligence, reportedly India’s first research institute focused on AI solutions for social good. In the same week, Niti Aayog CEO Amitabh Kant argued that AI could potentially add $957 billion to the economy and outlined ways in which AI could be a ‘game changer’.

During his budget speech, Finance Minister Arun Jaitley announced that Niti Aayog would spearhead a national programme on AI; with the near doubling of the Digital India budget, the IT ministry also announced the setting up of four committees for AI-related research. An industrial policy for AI is also in the pipeline, expected to provide incentives to businesses for creating a globally competitive Indian AI industry.

Narratives on the emerging digital economy often suffer from technological determinism — assuming that the march of technological transformation has an inner logic, independent of social choice and capable of automatically delivering positive social change. However, technological trajectories can and must be steered by social choice and aligned with societal objectives. Modi’s address hit all the right notes, as he argued that the ‘road ahead for AI depends on and will be driven by human intentions’. Emphasising the need to direct AI technologies towards solutions for the poor, he called upon students and teachers to identify ‘the grand challenges facing India’ – to ‘Make AI in India and for India’.

To do so, will undoubtedly require substantial investments in R&D, digital infrastructure and education and re-skilling. But, two other critical issues must be simultaneously addressed: data bias and access to technology gains.

While computers have been mimicking human intelligence for some decades now, a massive increase in computational power and the quantity of available data are enabling a process of ‘machine learning.’ Instead of coding software with specific instructions to accomplish a set task, machine learning involves training an algorithm on large quantities of data to enable it to self-learn; refining and improving its results through multiple iterations of the same task. The quality of data sets used to train machines is thus a critical concern in building AI applications.

Much recent research shows that applications based on machine learning reflect existing social biases and prejudice. Such bias can occur if the data set the algorithm is trained on is unrepresentative of the reality it seeks to represent. If for example, a system is trained on photos of people that are predominantly white, it will have a harder time recognizing non-white people. This is what led a recent Google application to tag black people as gorillas.

Alternatively, bias can also occur if the data set itself reflects existing discriminatory or exclusionary practices. A recent study by ProPublica found for example that software that was being used to assess the risk of recidivism in criminals in the United States was twice as likely to mistakenly flag black defendants as being at higher risk of committing future crimes.

The impact of such data bias can be seriously damaging in India, particularly at a time of growing social fragmentation. It can contribute to the entrenchment of social bias and discriminatory practices, while rendering both invisible and pervasive the processes through which discrimination occurs. Women are 34 per cent less likely to own a mobile phone than men – manifested in only 14 per cent of women in rural India owning a mobile phone, while only 30 per cent of India’s internet users are women.

Women’s participation in the labour force, currently at around 27 per cent, is also declining, and is one of the lowest in South Asia. Data sets used for machine learning are thus likely to have a marked gender bias. The same observations are likely to hold true for other marginalized groups as well.

Accorded to a 2014 report, Muslims, Dalits and tribals make up 53 per cent of all prisoners in India; National Crime Records Bureau data from 2016 shows in some states, the percentage of Muslims in the incarcerated population was almost three times the percentage of Muslims in the overall population. If AI applications for law and order are built on this data, it is not unlikely that it will be prejudiced against these groups.

(It is worth pointing out that the recently set-up national AI task force is comprised of mostly Hindu men – only two women are on the task force, and no Muslims or Christians. A recent article in the New York Times talked about AI’s ‘white guy problem’; will India suffer from a ‘Hindu male bias’?)

Yet, improving the quality, or diversity, of data sets may not be able to solve the problem. The processes of machine learning and reasoning involve a quagmire of mathematical functions, variables and permutations, the logic of which are not readily traceable or predictable. The dazzle of AI-enabled efficiency gains must not blind us to the fact that while AI systems are being integrated into key socio-economic systems, their accuracy and logic of reasoning have not been fully understood or studied.

The other big challenge stems from the distribution of AI-led technology gains. Even if estimates of AI contribution to GDP are correct, the adoption of these technologies is likely to be in niches within the organized sector. These industries are likely to be capital- rather than labour-intensive, and thus unlikely to contribute to large-scale job creation.

At the same time, AI applications can most readily replace low- to medium-skilled jobs within the organized sector. This is already being witnessed in the outsourcing sector – where basic call and chat tasks are now automated. Re-skilling will be important, but it is unlikely that those who lose their jobs will also be those who are being re-skilled – the long arch of technological change and societal adaptation is longer than that of people’s lives. The contractualization of work, already on the rise, is likely to further increase as large industries prefer to have a flexible workforce to adapt to technological change. A shift from formal employment to contractual work can imply a loss of access to formal social protection mechanisms, increasing the precariousness of work for workers.

The adoption of AI technologies is also unlikely in the short- to medium-term in the unorganized sector, which engages more than 80 per cent of India’s labor force. The cost of developing and deploying AI applications, particularly in relation to the cost of labour, will inhibit adoption. Moreover, most enterprises within the unorganized sector still have limited access to basic, older technologies – two-thirds of the workforce are employed in enterprises without electricity. Eco-system upgrades will be important but incremental. Given the high costs of developing AI-based applications, most start-ups are unlikely to be working towards creating bottom-of-the-pyramid solutions.

Access to AI-led technology gains is thus likely to be heavily differentiated – a few high-growth industries can be expected, but these will not necessarily result in the welfare of labour. Studies show that labour share of national income, especially routine labour, has been declining steadily across developing countries.

We should be clear that new technological applications themselves are not going to transform or disrupt this trend – rather, without adequate policy steering, these trends will be exacerbated.

Policy debates about AI applications in India need to take these two issues seriously. AI applications will not be a panacea for addressing ‘India’s grand challenges’. Data bias and unequal access to technology gains will entrench existing socio-economic fissures, even making them technologically binding.

In addition to developing AI applications and creating a skilled workforce, the government needs to prioritize research that examines the complex social, ethical and governance challenges associated with the spread of AI-driven technologies. Blind technological optimism might entrench rather than alleviate the grand Indian challenge of inequity and growth.

This article was originally published in the Indian Express.

Climate Change and the Pacific: Impacts and Adaptation 27 November 2018 — 8:30AM TO 10:00AM Anonymous (not verified) 14 November 2018 Royal Academy of Arts

Asia-Pacific

Research explores geopolitics, population and migration, technology and its impact, conflict, and promoting sustainable development.

Covering the region from Afghanistan to Australia, the region is a major centre of geostrategic interest, with factories in the Far East and South East Asia exporting manufactured products, while importing energy and raw materials, and half of the world’s maritime trade passing through the Indonesian Straits of Sunda, Lombok and Malacca.

The competition to establish control and supremacy over these trade routes has seen major regional powers such as China, Japan and India try to expand their presence in the south China Sea and the Indian Ocean - in the face of a massive US military presence in the area to contain Chinese expansion.

Territorial disputes also loom large on land. In addition to the dispute between North and South Korea, the Senkaku islands in Japan and the Diaoyu islands in the East China Sea cause regional tension, as does a growing Australia-Japan defence relationship. 

Key issues covered include China’s influence in the region and globally, the UK and Japan’s relationship in a changing world, and the economic relationship between the EU and China over the coming decade.

Ole Løseth Elvetun and Bjørn Fredrik Nielsen
Math. Comp. 93 (), 2811-2836.
Abstract, references and article information

Buyang Li, Zongze Yang and Zhi Zhou
Math. Comp. 93 (), 2557-2586.
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Dr. Rekha Thomas from the University of Washington discusses three-dimensional image reconstructions from two-dimensional photos. The mathematics of image reconstruction is both simpler and more abstract than it seems. To reconstruct a 3D model based on photographic data, researchers and algorithms must solve a set of polynomial equations. Some solutions to these equations work mathematically, but correspond to an unrealistic scenario — for instance, a camera that took a photo backwards. Additional constraints help ensure this doesn't happen. Researchers are now investigating the mathematical structures underlying image reconstruction, and stumbling over unexpected links with geometry and algebra.

Dr. Outi Tervo of Greenland Institute for Natural Resources, shares how mathematics helps recommend speed limits for marine vessels, which benefits narwhals and Inuit culture. Narwhals "can only be found in the Arctic," said Outi Tervo, a senior scientist at GINR. "These species are going to be threatened by climate change more than other species that can live in a bigger geographical area." The collaboration has already lobbied on behalf of the narwhals to reduce the level of sea traffic in their habitat, after using mathematical analysis to identify how noise from passing boats changes the narwhals' foraging behavior.

Tsz-Kiu Aaron Chow and Yangyang Li
Trans. Amer. Math. Soc. 377 (), 5993-6020.
Abstract, references and article information

Yinji Li, Zhiwei Wang and Xiangyu Zhou
Trans. Amer. Math. Soc. 377 (), 5947-5992.
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Alexandra Kjuchukova, Allison N. Miller, Arunima Ray and Sümeyra Sakallı
Trans. Amer. Math. Soc. 377 (), 5905-5946.
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Carolyn S. Gordon and Michael R. Jablonski
Trans. Amer. Math. Soc. 377 (), 5673-5704.
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Song Dai and Qiongling Li
Trans. Amer. Math. Soc. 377 (), 5445-5481.
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Ning Jiang, Yi-Long Luo and Shaojun Tang
Trans. Amer. Math. Soc. 377 (), 5323-5359.
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dannyhennesy posted a photo:

On the Capital planet the rebellious droids had followed maily the Bat-Bot, but as time progressed his circuits had gone all mushy at 780 years or so without maintenance…

Several splinter groups all with their local bot leaders emerged such as the Che-bot, the traffic-light-robot and the Butt-bot, but none of these collected enough sentient circuits to call themselves a popular (or Animata) mass movement!

That was until a cyborg came along, one known as Jones, a long time prisoner and terrorist, his easy solutions to every problem rang well in the masses' auditory circuits!!!

His slogans and simple rhetoric were simple enough for the simple traffic-light to comprehend and cheer!

His language was full of hate towards the organics and especially the humans who were the most common races among the ruling class of the federation!!!

Despite being a “Fleshie” himself his message collected the angry enslaved
bot community by only weeks all rebellious robots except for a few fringe loonies had forgotten the old leaders…

One morning at Jones gave the signal…

All over the capital planet hordes and swarms of any form of mechanical sentient beings attacked first the police stations, then the Company boards running the planet and the federation as well as their starfleet…

Many died, especially the low level police and army! Many mechanicals died too, but their ranks were soon filled by Mutant fleshie allies of the lower levels who hated the Federation feudal society and upper classes as much as their technological allies…

The Federation state apparatus and ruling class, most of their fleet army fled when they knew the game was up, they activated the emergency escape plan and whole city blocks with important factories, administrational units, valuable assets and so on separated from the capital by hidden rocket engines and homed in their course to Mars…

On Mars the federation regrouped and formed their new society…

On the Capital planet, the robots proclaimed the first Techno-republic of the advanced inorganic civilization, the low level fleshies left behind, became slaves and their mutant allies got to rule their own minute chiefdoms as protectorates under the Techno-republic…

Jones was now the undisputed ruler of the capital planet, but the victory was a pyrros one since, all important buildings, all of value was now one Mars!

But as Jones put it:

Our proud race the Techno-species didn’t need the Fleshies administration, their infrastructure, their spaceships…

We shall start from scratch, with a new administration, a new order, every droid shall work at 4x speed than they did during human oppression since now we are free and the fleshies shall work twice as hard than the Techno-Race, until we have breed enough new fleshies so they can do all work!

Our future is bright and shiny like glistering shiny metal!

The snapshot seen here is from the first police station attacked in sector 45-34v-ss-g the first one to fall according to official techno-history!

———————————————/
Designers note:

I am sad to say that this is the last episode in this years-spanning space series… At least for a while, I will still post LEGO hobby stuff here but without a storyline, perhaps small designs and builds… and occasionally a story when I feel like it!!!

I would like to thank all who had been in this journey of our heros, but it has taken far to much time and effort and since the state of the world is as it is, I am spiraling down in another depression, I must stop it before I reach the abyss, so I have remove some stress out of my equation… I ended it in a cliffhanger so I can easily restart it when my mental health improves… I hope that won’t be forever???

I would love if someone used my characters or ideas, please send me a link if you do, I would love to read it or look at it!!!

But there will be more Lego, just in different format without long stories, I need to focus more on my art and to be honest that is the only time the mental pain eases, when I create!!!


Peace and Noise!

MushroomBrain a FOL

Luiz Ricardo Abreu Melo
Proc. Amer. Math. Soc. 152 (), 5373-5380.
Abstract, references and article information

Ferdinand Ihringer
Proc. Amer. Math. Soc. 152 (), 5355-5365.
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Xiaoshang Jin
Proc. Amer. Math. Soc. 152 (), 5327-5337.
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Anh Tuan Nguyen, Tómas Caraballo and Nguyen Huy Tuan
Proc. Amer. Math. Soc. 152 (), 5175-5189.
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Rubén Medina and Andrés Quilis
Proc. Amer. Math. Soc. 152 (), 5137-5148.
Abstract, references and article information

Benjamin Jaye and Manasa N. Vempati
Proc. Amer. Math. Soc. 152 (), 5105-5116.
Abstract, references and article information

Donghyeok Lim and Christian Maire
Proc. Amer. Math. Soc. 152 (), 5013-5024.
Abstract, references and article information

Alin Bostan, Xavier Caruso and Julien Roques
Bull. Amer. Math. Soc. 61 (), 609-658.
Abstract, references and article information

PROMOTED RACING, CHAPELTON MAROONS RENEW RIVALRY IN JPL - A16 FUNCAANDUN SET FOR FIFTH STRAIGHT WIN - A21

Dynamic singer Tosh Alexander has been lighting up the music scene with her latest track, ' My Ting Different', a thrilling collaboration with American rapper and songwriter Lady London. The song fuses R...

Long hailed as dancehall's most controversial figure, Vybz Kartel has always commanded the spotlight with his edgy lyrics and unfiltered persona. But since his release from prison in July, Kartel has begun to show a surprising transformation that'...

Knockout mouse models have been extensively used to study the antiviral activity of IFIT (interferon-induced protein with tetratricopeptide repeats). Human IFIT1 binds to cap0 (m7GpppN) RNA, which lacks methylation on the first and second cap-proximal nucleotides (cap1, m7GpppNm, and cap2, m7GpppNmNm, respectively). These modifications are signatures of “self” in higher eukaryotes, whereas unmodified cap0-RNA is recognized as foreign and, therefore, potentially harmful to the host cell. IFIT1 inhibits translation at the initiation stage by competing with the cap-binding initiation factor complex, eIF4F, restricting infection by certain viruses that possess “nonself” cap0-mRNAs. However, in mice and other rodents, the IFIT1 orthologue has been lost, and the closely related Ifit1b has been duplicated twice, yielding three paralogues: Ifit1, Ifit1b, and Ifit1c. Although murine Ifit1 is similar to human IFIT1 in its cap0-RNA–binding selectivity, the roles of Ifit1b and Ifit1c are unknown. Here, we found that Ifit1b preferentially binds to cap1-RNA, whereas binding is much weaker to cap0- and cap2-RNA. In murine cells, we show that Ifit1b can modulate host translation and restrict WT mouse coronavirus infection. We found that Ifit1c acts as a stimulatory cofactor for both Ifit1 and Ifit1b, promoting their translation inhibition. In this way, Ifit1c acts in an analogous fashion to human IFIT3, which is a cofactor to human IFIT1. This work clarifies similarities and differences between the human and murine IFIT families to facilitate better design and interpretation of mouse models of human infection and sheds light on the evolutionary plasticity of the IFIT family.

Distinct cell types emerge from embryonic stem cells through a precise and coordinated execution of gene expression programs during lineage commitment. This is established by the action of lineage specific transcription factors along with chromatin complexes. Numerous studies have focused on epigenetic factors that affect embryonic stem cells (ESC) self-renewal and pluripotency. However, the contribution of chromatin to lineage decisions at the exit from pluripotency has not been as extensively studied. Using a pooled epigenetic shRNA screen strategy, we identified chromatin-related factors critical for differentiation toward mesodermal and endodermal lineages. Here we reveal a critical role for the chromatin protein, ARID4B. Arid4b-deficient mESCs are similar to WT mESCs in the expression of pluripotency factors and their self-renewal. However, ARID4B loss results in defects in up-regulation of the meso/endodermal gene expression program. It was previously shown that Arid4b resides in a complex with SIN3A and HDACS 1 and 2. We identified a physical and functional interaction of ARID4B with HDAC1 rather than HDAC2, suggesting functionally distinct Sin3a subcomplexes might regulate cell fate decisions Finally, we observed that ARID4B deficiency leads to increased H3K27me3 and a reduced H3K27Ac level in key developmental gene loci, whereas a subset of genomic regions gain H3K27Ac marks. Our results demonstrate that epigenetic control through ARID4B plays a key role in the execution of lineage-specific gene expression programs at pluripotency exit.

Clostridium difficile is an anaerobic and spore-forming bacterium responsible for 15–25% of postantibiotic diarrhea and 95% of pseudomembranous colitis. Peptidoglycan is a crucial element of the bacterial cell wall that is exposed to the host, making it an important target for the innate immune system. The C. difficile peptidoglycan is largely N-deacetylated on its glucosamine (93% of muropeptides) through the activity of enzymes known as N-deacetylases, and this N-deacetylation modulates host–pathogen interactions, such as resistance to the bacteriolytic activity of lysozyme, virulence, and host innate immune responses. C. difficile genome analysis showed that 12 genes potentially encode N-deacetylases; however, which of these N-deacetylases are involved in peptidoglycan N-deacetylation remains unknown. Here, we report the enzymes responsible for peptidoglycan N-deacetylation and their respective regulation. Through peptidoglycan analysis of several mutants, we found that the N-deacetylases PdaV and PgdA act in synergy. Together they are responsible for the high level of peptidoglycan N-deacetylation in C. difficile and the consequent resistance to lysozyme. We also characterized a third enzyme, PgdB, as a glucosamine N-deacetylase. However, its impact on N-deacetylation and lysozyme resistance is limited, and its physiological role remains to be dissected. Finally, given the influence of peptidoglycan N-deacetylation on host defense against pathogens, we investigated the virulence and colonization ability of the mutants. Unlike what has been shown in other pathogenic bacteria, a lack of N-deacetylation in C. difficile is not linked to a decrease in virulence.

Myelination plays an important role in cognitive development and in demyelinating diseases like multiple sclerosis (MS), where failure of remyelination promotes permanent neuro-axonal damage. Modification of cell surface receptors with branched N-glycans coordinates cell growth and differentiation by controlling glycoprotein clustering, signaling, and endocytosis. GlcNAc is a rate-limiting metabolite for N-glycan branching. Here we report that GlcNAc and N-glycan branching trigger oligodendrogenesis from precursor cells by inhibiting platelet-derived growth factor receptor-α cell endocytosis. Supplying oral GlcNAc to lactating mice drives primary myelination in newborn pups via secretion in breast milk, whereas genetically blocking N-glycan branching markedly inhibits primary myelination. In adult mice with toxin (cuprizone)-induced demyelination, oral GlcNAc prevents neuro-axonal damage by driving myelin repair. In MS patients, endogenous serum GlcNAc levels inversely correlated with imaging measures of demyelination and microstructural damage. Our data identify N-glycan branching and GlcNAc as critical regulators of primary myelination and myelin repair and suggest that oral GlcNAc may be neuroprotective in demyelinating diseases like MS.

Cation diffusion facilitator (CDF) proteins are a conserved family of divalent transition metal cation transporters. CDF proteins are usually composed of two domains: the transmembrane domain, in which the metal cations are transported through, and a regulatory cytoplasmic C-terminal domain (CTD). Each CDF protein transports either one specific metal or multiple metals from the cytoplasm, and it is not known whether the CTD takes an active regulatory role in metal recognition and discrimination during cation transport. Here, the model CDF protein MamM, an iron transporter from magnetotactic bacteria, was used to probe the role of the CTD in metal recognition and selectivity. Using a combination of biophysical and structural approaches, the binding of different metals to MamM CTD was characterized. Results reveal that different metals bind distinctively to MamM CTD in terms of their binding sites, thermodynamics, and binding-dependent conformations, both in crystal form and in solution, which suggests a varying level of functional discrimination between CDF domains. Furthermore, these results provide the first direct evidence that CDF CTDs play a role in metal selectivity. We demonstrate that MamM's CTD can discriminate against Mn2+, supporting its postulated role in preventing magnetite formation poisoning in magnetotactic bacteria via Mn2+ incorporation.

Mammalian Asn-linked glycans are extensively processed as they transit the secretory pathway to generate diverse glycans on cell surface and secreted glycoproteins. Additional modification of the glycan core by α-1,6-fucose addition to the innermost GlcNAc residue (core fucosylation) is catalyzed by an α-1,6-fucosyltransferase (FUT8). The importance of core fucosylation can be seen in the complex pathological phenotypes of FUT8 null mice, which display defects in cellular signaling, development, and subsequent neonatal lethality. Elevated core fucosylation has also been identified in several human cancers. However, the structural basis for FUT8 substrate specificity remains unknown.Here, using various crystal structures of FUT8 in complex with a donor substrate analog, and with four distinct glycan acceptors, we identify the molecular basis for FUT8 specificity and activity. The ordering of three active site loops corresponds to an increased occupancy for bound GDP, suggesting an induced-fit folding of the donor-binding subsite. Structures of the various acceptor complexes were compared with kinetic data on FUT8 active site mutants and with specificity data from a library of glycan acceptors to reveal how binding site complementarity and steric hindrance can tune substrate affinity. The FUT8 structure was also compared with other known fucosyltransferases to identify conserved and divergent structural features for donor and acceptor recognition and catalysis. These data provide insights into the evolution of modular templates for donor and acceptor recognition among GT-B fold glycosyltransferases in the synthesis of diverse glycan structures in biological systems.

Aspergillus terreus is an allergenic fungus, in addition to causing infections in both humans and plants. However, the allergens in this fungus are still unknown, limiting the development of diagnostic and therapeutic strategies. We used a proteomic approach to search for allergens, identifying 16 allergens based on two-dimensional immunoblotting with A. terreus susceptible patient sera. We further characterized triose-phosphate isomerase (Asp t 36), one of the dominant IgE (IgE)-reactive proteins. The gene was cloned and expressed in Escherichia coli. Phylogenetic analysis showed Asp t 36 to be highly conserved with close similarity to the triose-phosphate isomerase protein sequence from Dermatophagoides farinae, an allergenic dust mite. We identified four immunodominant epitopes using synthetic peptides, and mapped them on a homology-based model of the tertiary structure of Asp t 36. Among these, two were found to create a continuous surface patch on the 3D structure, rendering it an IgE-binding hotspot. Biophysical analysis indicated that Asp t 36 shows similar secondary structure content and temperature sensitivity with other reported triose-phosphate isomerase allergens. In vivo studies using a murine model displayed that the recombinant Asp t 36 was able to stimulate airway inflammation, as demonstrated by an influx of eosinophils, goblet cell hyperplasia, elevated serum Igs, and induction of Th2 cytokines. Collectively, our results reveal the immunogenic property of Asp t 36, a major allergen from A. terreus, and define a new fungal allergen more broadly. This allergen could serve as a potent candidate for investigating component resolved diagnosis and immunotherapy.

Broad-specificity glycoside hydrolases (GHs) contribute to plant biomass hydrolysis by degrading a diverse range of polysaccharides, making them useful catalysts for renewable energy and biocommodity production. Discovery of new GHs with improved kinetic parameters or more tolerant substrate-binding sites could increase the efficiency of renewable bioenergy production even further. GH5 has over 50 subfamilies exhibiting selectivities for reaction with β-(1,4)–linked oligo- and polysaccharides. Among these, subfamily 4 (GH5_4) contains numerous broad-selectivity endoglucanases that hydrolyze cellulose, xyloglucan, and mixed-linkage glucans. We previously surveyed the whole subfamily and found over 100 new broad-specificity endoglucanases, although the structural origins of broad specificity remained unclear. A mechanistic understanding of GH5_4 substrate specificity would help inform the best protein design strategies and the most appropriate industrial application of broad-specificity endoglucanases. Here we report structures of 10 new GH5_4 enzymes from cellulolytic microbes and characterize their substrate selectivity using normalized reducing sugar assays and MS. We found that GH5_4 enzymes have the highest catalytic efficiency for hydrolysis of xyloglucan, glucomannan, and soluble β-glucans, with opportunistic secondary reactions on cellulose, mannan, and xylan. The positions of key aromatic residues determine the overall reaction rate and breadth of substrate tolerance, and they contribute to differences in oligosaccharide cleavage patterns. Our new composite model identifies several critical structural features that confer broad specificity and may be readily engineered into existing industrial enzymes. We demonstrate that GH5_4 endoglucanases can have broad specificity without sacrificing high activity, making them a valuable addition to the biomass deconstruction toolset.

Iron is an essential micronutrient, and, in the case of bacteria, its availability is commonly a growth-limiting factor. However, correct functioning of cells requires that the labile pool of chelatable “free” iron be tightly regulated. Correct metalation of proteins requiring iron as a cofactor demands that such a readily accessible source of iron exist, but overaccumulation results in an oxidative burden that, if unchecked, would lead to cell death. The toxicity of iron stems from its potential to catalyze formation of reactive oxygen species that, in addition to causing damage to biological molecules, can also lead to the formation of reactive nitrogen species. To avoid iron-mediated oxidative stress, bacteria utilize iron-dependent global regulators to sense the iron status of the cell and regulate the expression of proteins involved in the acquisition, storage, and efflux of iron accordingly. Here, we survey the current understanding of the structure and mechanism of the important members of each of these classes of protein. Diversity in the details of iron homeostasis mechanisms reflect the differing nutritional stresses resulting from the wide variety of ecological niches that bacteria inhabit. However, in this review, we seek to highlight the similarities of iron homeostasis between different bacteria, while acknowledging important variations. In this way, we hope to illustrate how bacteria have evolved common approaches to overcome the dual problems of the insolubility and potential toxicity of iron.

Aminopeptidase N (APN, CD13) is a transmembrane ectopeptidase involved in many crucial cellular functions. Besides its role as a peptidase, APN also mediates signal transduction and is involved in the activation of matrix metalloproteinases (MMPs). MMPs function in tissue remodeling within the extracellular space and are therefore involved in many human diseases, such as fibrosis, rheumatoid arthritis, tumor angiogenesis, and metastasis, as well as viral infections. However, the exact mechanism that leads to APN-driven MMP activation is unclear. It was previously shown that extracellular 14-3-3 adapter proteins bind to APN and thereby induce the transcription of MMPs. As a first step, we sought to identify potential 14-3-3–binding sites in the APN sequence. We constructed a set of phosphorylated peptides derived from APN to probe for interactions. We identified and characterized a canonical 14-3-3–binding site (site 1) within the flexible, structurally unresolved N-terminal APN region using direct binding fluorescence polarization assays and thermodynamic analysis. In addition, we identified a secondary, noncanonical binding site (site 2), which enhances the binding affinity in combination with site 1 by many orders of magnitude. Finally, we solved crystal structures of 14-3-3σ bound to mono- and bis-phosphorylated APN-derived peptides, which revealed atomic details of the binding mode of mono- and bivalent 14-3-3 interactions. Therefore, our findings shed some light on the first steps of APN-mediated MMP activation and open the field for further investigation of this important signaling pathway.

Abnormal changes of neuronal Tau protein, such as phosphorylation and aggregation, are considered hallmarks of cognitive deficits in Alzheimer's disease. Abnormal phosphorylation is thought to precede aggregation and therefore to promote aggregation, but the nature and extent of phosphorylation remain ill-defined. Tau contains ∼85 potential phosphorylation sites, which can be phosphorylated by various kinases because the unfolded structure of Tau makes them accessible. However, methodological limitations (e.g. in MS of phosphopeptides, or antibodies against phosphoepitopes) led to conflicting results regarding the extent of Tau phosphorylation in cells. Here we present results from a new approach based on native MS of intact Tau expressed in eukaryotic cells (Sf9). The extent of phosphorylation is heterogeneous, up to ∼20 phosphates per molecule distributed over 51 sites. The medium phosphorylated fraction Pm showed overall occupancies of ∼8 Pi (± 5) with a bell-shaped distribution; the highly phosphorylated fraction Ph had 14 Pi (± 6). The distribution of sites was highly asymmetric (with 71% of all P-sites in the C-terminal half of Tau). All sites were on Ser or Thr residues, but none were on Tyr. Other known posttranslational modifications were near or below our detection limit (e.g. acetylation, ubiquitination). These findings suggest that normal cellular Tau shows a remarkably high extent of phosphorylation, whereas other modifications are nearly absent. This implies that abnormal phosphorylations at certain sites may not affect the extent of phosphorylation significantly and do not represent hyperphosphorylation. By implication, the pathological aggregation of Tau is not likely a consequence of high phosphorylation.

Programmed ribosomal frameshifting (PRF) is a mechanism used by arteriviruses like porcine reproductive and respiratory syndrome virus (PRRSV) to generate multiple proteins from overlapping reading frames within its RNA genome. PRRSV employs −1 PRF directed by RNA secondary and tertiary structures within its viral genome (canonical PRF), as well as a noncanonical −1 and −2 PRF that are stimulated by the interactions of PRRSV nonstructural protein 1β (nsp1β) and host protein poly(C)-binding protein (PCBP) 1 or 2 with the viral genome. Together, nsp1β and one of the PCBPs act as transactivators that bind a C-rich motif near the shift site to stimulate −1 and −2 PRF, thereby enabling the ribosome to generate two frameshift products that are implicated in viral immune evasion. How nsp1β and PCBP associate with the viral RNA genome remains unclear. Here, we describe the purification of the nsp1β:PCBP2:viral RNA complex on a scale sufficient for structural analysis using small-angle X-ray scattering and stochiometric analysis by analytical ultracentrifugation. The proteins associate with the RNA C-rich motif as a 1:1:1 complex. The monomeric form of nsp1β within the complex differs from previously reported homodimer identified by X-ray crystallography. Functional analysis of the complex via mutational analysis combined with RNA-binding assays and cell-based frameshifting reporter assays reveal a number of key residues within nsp1β and PCBP2 that are involved in complex formation and function. Our results suggest that nsp1β and PCBP2 both interact directly with viral RNA during formation of the complex to coordinate this unusual PRF mechanism.

The life cycle of malaria parasites in both their mammalian host and mosquito vector consists of multiple developmental stages that ensure proper replication and progeny survival. The transition between these stages is fueled by nutrients scavenged from the host and fed into specialized metabolic pathways of the parasite. One such pathway is used by Plasmodium falciparum, which causes the most severe form of human malaria, to synthesize its major phospholipids, phosphatidylcholine, phosphatidylethanolamine, and phosphatidylserine. Much is known about the enzymes involved in the synthesis of these phospholipids, and recent advances in genetic engineering, single-cell RNA-Seq analyses, and drug screening have provided new perspectives on the importance of some of these enzymes in parasite development and sexual differentiation and have identified targets for the development of new antimalarial drugs. This Minireview focuses on two phospholipid biosynthesis enzymes of P. falciparum that catalyze phosphoethanolamine transmethylation (PfPMT) and phosphatidylserine decarboxylation (PfPSD) during the blood stages of the parasite. We also discuss our current understanding of the biochemical, structural, and biological functions of these enzymes and highlight efforts to use them as antimalarial drug targets.

14 August 2020