Human milk immune factors, maternal nutritional status, and infant sex: The INSPIRE study.

OBJECTIVES: Breastfeeding is an energetically costly and intense form of human parental investment, providing sole-source nutrition in early infancy and bioactive components, including immune factors. Given the energetic cost of lactation, milk factors may be subject to tradeoffs, and variation in concentrations have been explored utilizing the Trivers-Willard hypothesis. As human milk immune factors are critical to developing immune system and protect infants against pathogens, we tested whether concentrations of milk immune factors (IgA, IgM, IgG, EGF, TGFß2, and IL-10) vary in response to infant sex and maternal condition (proxied by maternal diet diversity [DD] and body mass index [BMI]) as posited in the Trivers-Willard hypothesis and consider the application of the hypothesis to milk composition. METHODS: We analyzed concentrations of immune factors in 358 milk samples collected from women residing in 10 international sites using linear mixed-effects models to test for an interaction between maternal condition, including population as a random effect and infant age and maternal age as fixed effects. RESULTS: IgG concentrations were significantly lower in milk produced by women consuming diets with low diversity with male infants than those with female infants. No other significant associations were identified. CONCLUSIONS: IgG concentrations were related to infant sex and maternal diet diversity, providing minimal support for the hypothesis. Given the lack of associations across other select immune factors, results suggest that the Trivers-Willard hypothesis may not be broadly applied to human milk immune factors as a measure of maternal investment, which are likely buffered against perturbations in maternal condition.

A Study on the Nature of SARS-CoV-2 Using the Shell Disorder Models: Reproducibility, Evolution, Spread, and Attenuation.

The basic tenets of the shell disorder model (SDM) as applied to COVID-19 are that the harder outer shell of the virus shell (lower PID-percentage of intrinsic disorder-of the membrane protein M, PIDM) and higher flexibility of the inner shell (higher PID of the nucleocapsid protein N, PIDN) are correlated with the contagiousness and virulence, respectively. M protects the virion from the anti-microbial enzymes in the saliva and mucus. N disorder is associated with the rapid replication of the virus. SDM predictions are supported by two experimental observations. The first observation demonstrated lesser and greater presence of the Omicron particles in the lungs and bronchial tissues, respectively, as there is a greater level of mucus in the bronchi. The other observation revealed that there are lower viral loads in 2017-pangolin-CoV, which is predicted to have similarly low PIDN as Omicron. The abnormally hard M, which is very rarely seen in coronaviruses, arose from the fecal-oral behaviors of pangolins via exposure to buried feces. Pangolins provide an environment for coronavirus (CoV) attenuation, which is seen in Omicron. Phylogenetic study using M shows that COVID-19-related bat-CoVs from Laos and Omicron are clustered in close proximity to pangolin-CoVs, which suggests the recurrence of interspecies transmissions. Hard M may have implications for long COVID-19, with immune systems having difficulty degrading viral proteins/particles.

Comprehensive Phylogenomics of Methylobacterium Reveals Four Evolutionary Distinct Groups and Underappreciated Phyllosphere Diversity.

Methylobacterium is a group of methylotrophic microbes associated with soil, fresh water, and particularly the phyllosphere, the aerial part of plants that has been well studied in terms of physiology but whose evolutionary history and taxonomy are unclear. Recent work has suggested that Methylobacterium is much more diverse than thought previously, questioning its status as an ecologically and phylogenetically coherent taxonomic genus. However, taxonomic and evolutionary studies of Methylobacterium have mostly been restricted to model species, often isolated from habitats other than the phyllosphere and have yet to utilize comprehensive phylogenomic methods to examine gene trees, gene content, or synteny. By analyzing 189 Methylobacterium genomes from a wide range of habitats, including the phyllosphere, we inferred a robust phylogenetic tree while explicitly accounting for the impact of horizontal gene transfer (HGT). We showed that Methylobacterium contains four evolutionarily distinct groups of bacteria (namely A, B, C, D), characterized by different genome size, GC content, gene content, and genome architecture, revealing the dynamic nature of Methylobacterium genomes. In addition to recovering 59 described species, we identified 45 candidate species, mostly phyllosphere-associated, stressing the significance of plants as a reservoir of Methylobacterium diversity. We inferred an ancient transition from a free-living lifestyle to association with plant roots in Methylobacteriaceae ancestor, followed by phyllosphere association of three of the major groups (A, B, D), whose early branching in Methylobacterium history has been heavily obscured by HGT. Together, our work lays the foundations for a thorough redefinition of Methylobacterium taxonomy, beginning with the abandonment of Methylorubrum.

Shell Disorder Models Detect That Omicron Has Harder Shells with Attenuation but Is Not a Descendant of the Wuhan-Hu-1 SARS-CoV-2.

Before the SARS-CoV-2 Omicron variant emergence, shell disorder models (SDM) suggested that an attenuated precursor from pangolins may have entered humans in 2017 or earlier. This was based on a shell disorder analysis of SARS-CoV-1/2 and pangolin-Cov-2017. The SDM suggests that Omicron is attenuated with almost identical N (inner shell) disorder as pangolin-CoV-2017 (N-PID (percentage of intrinsic disorder): 44.8% vs. 44.9%-lower than other variants). The outer shell disorder (M-PID) of Omicron is lower than that of other variants and pangolin-CoV-2017 (5.4% vs. 5.9%). COVID-19-related CoVs have the lowest M-PIDs (hardest outer shell) among all CoVs. This is likely to be responsible for the higher contagiousness of SARS-CoV-2 and Omicron, since hard outer shell protects the virion from salivary/mucosal antimicrobial enzymes. Phylogenetic study using M reveals that Omicron branched off from an ancestor of the Wuhan-Hu-1 strain closely related to pangolin-CoVs. M, being evolutionarily conserved in COVID-19, is most ideal for COVID-19 phylogenetic study. Omicron may have been hiding among burrowing animals (e.g., pangolins) that provide optimal evolutionary environments for attenuation and increase shell hardness, which is essential for fecal-oral-respiratory transmission via buried feces. Incoming data support SDM e.g., the presence of fewer infectious particles in the lungs than in the bronchi upon infection.

Computational, Experimental, and Clinical Evidence of a Specific but Peculiar Evolutionary Nature of (COVID-19) SARS-CoV-2.

The shell disorder models have predicted that SARS-CoV-2 is of a specific but peculiar evolutionary nature. All coronaviruses (CoVs) closely related to SARS-CoV-2 have been found to have the hardest outer shells (M protein) among CoVs. This hard shell (low M percentage of intrinsic disorder (PID)) is associated with burrowing animals, for example, pangolins, and is believed to be responsible for the high contagiousness of SARS-CoV-2 because it will be more resistant to antimicrobial enzymes found in saliva/mucus. Incoming clinical and experimental data do support this along with a prediction based on another aspect of the shell (N, inner shell) disorder models that SARS-CoV-1 is more virulent than SARS-CoV-2 because SARS-CoV-2 produces fewer virus copies in vital organs even if large amounts of infections particles are shed orally and nasally. A phylogenetic study using M reveals a closer relationship of SARS-CoV to pangolin-CoVs than the bat-RaTG13 found in Yunnan, China. Previous studies may have been confused by recombinations that were poorly handled. The shell disorder models suggest that a pangolin-CoV strain may have entered the human population in 2017 or before as an attenuated virus, which could explain why SARS-CoV is found to be highly adapted to humans.

Fine-Scale Adaptations to Environmental Variation and Growth Strategies Drive Phyllosphere Methylobacterium Diversity.

Methylobacterium is a prevalent bacterial genus of the phyllosphere. Despite its ubiquity, little is known about the extent to which its diversity reflects neutral processes like migration and drift, versus environmental filtering of life history strategies and adaptations. In two temperate forests, we investigated how phylogenetic diversity within Methylobacterium is structured by biogeography, seasonality, and growth strategies. Using deep, culture-independent barcoded marker gene sequencing coupled with culture-based approaches, we uncovered a considerable diversity of Methylobacterium in the phyllosphere. We cultured different subsets of Methylobacterium lineages depending upon the temperature of isolation and growth (20°C or 30°C), suggesting long-term adaptation to temperature. To a lesser extent than temperature adaptation, Methylobacterium diversity was also structured across large (>100 km; between forests) and small (<1.2 km; within forests) geographical scales, among host tree species, and was dynamic over seasons. By measuring the growth of 79 isolates during different temperature treatments, we observed contrasting growth performances, with strong lineage- and season-dependent variations in growth strategies. Finally, we documented a progressive replacement of lineages with a high-yield growth strategy typical of cooperative, structured communities in favor of those characterized by rapid growth, resulting in convergence and homogenization of community structure at the end of the growing season. Together, our results show how Methylobacterium is phylogenetically structured into lineages with distinct growth strategies, which helps explain their differential abundance across regions, host tree species, and time. This work paves the way for further investigation of adaptive strategies and traits within a ubiquitous phyllosphere genus. IMPORTANCE Methylobacterium is a bacterial group tied to plants. Despite the ubiquity of methylobacteria and the importance to their hosts, little is known about the processes driving Methylobacterium community dynamics. By combining traditional culture-dependent and -independent (metabarcoding) approaches, we monitored Methylobacterium diversity in two temperate forests over a growing season. On the surface of tree leaves, we discovered remarkably diverse and dynamic Methylobacterium communities over short temporal (from June to October) and spatial (within 1.2 km) scales. Because we cultured different subsets of Methylobacterium diversity depending on the temperature of incubation, we suspected that these dynamics partly reflected climatic adaptation. By culturing strains under laboratory conditions mimicking seasonal variations, we found that diversity and environmental variations were indeed good predictors of Methylobacterium growth performances. Our findings suggest that Methylobacterium community dynamics at the surface of tree leaves results from the succession of strains with contrasting growth strategies in response to environmental variations.

No-boundary thinking: a viable solution to ethical data-driven AI in precision medicine.

Today Artificial Intelligence (AI) supports difficult decisions about policy, health, and our personal lives. The AI algorithms we develop and deploy to make sense of information, are informed by data, and based on models that capture and use pertinent details of the population or phenomenon being analyzed. For any application area, more importantly in precision medicine which directly impacts human lives, the data upon which algorithms are run must be procured, cleaned, and organized well to assure reliable and interpretable results, and to assure that they do not perpetrate or amplify human prejudices. This must be done without violating basic assumptions of the algorithms in use. Algorithmic results need to be clearly communicated to stakeholders and domain experts to enable sound conclusions. Our position is that AI holds great promise for supporting precision medicine, but we need to move forward with great care, with consideration for possible ethical implications. We make the case that a no-boundary or convergent approach is essential to support sound and ethical decisions. No-boundary thinking supports problem definition and solving with teams of experts possessing diverse perspectives. When dealing with AI and the data needed to use AI, there is a spectrum of activities that needs the attention of a no-boundary team. This is necessary if we are to draw viable conclusions and develop actions and policies based on the AI, the data, and the scientific foundations of the domain in question.

Variation in Human Milk Composition Is Related to Differences in Milk and Infant Fecal Microbial Communities.

Previously published data from our group and others demonstrate that human milk oligosaccharide (HMOs), as well as milk and infant fecal microbial profiles, vary by geography. However, little is known about the geographical variation of other milk-borne factors, such as lactose and protein, as well as the associations among these factors and microbial community structures in milk and infant feces. Here, we characterized and contrasted concentrations of milk-borne lactose, protein, and HMOs, and examined their associations with milk and infant fecal microbiomes in samples collected in 11 geographically diverse sites. Although geographical site was strongly associated with milk and infant fecal microbiomes, both sample types assorted into a smaller number of community state types based on shared microbial profiles. Similar to HMOs, concentrations of lactose and protein also varied by geography. Concentrations of HMOs, lactose, and protein were associated with differences in the microbial community structures of milk and infant feces and in the abundance of specific taxa. Taken together, these data suggest that the composition of human milk, even when produced by relatively healthy women, differs based on geographical boundaries and that concentrations of HMOs, lactose, and protein in milk are related to variation in milk and infant fecal microbial communities.

Key genetic variants associated with variation of milk oligosaccharides from diverse human populations.

Human milk oligosaccharides (HMO), the third most abundant component of human milk, are thought to be important contributors to infant health. Studies have provided evidence that geography, stage of lactation, and Lewis and secretor blood groups are associated with HMO profile. However, little is known about how variation across the genome may influence HMO composition among women in various populations. In this study, we performed genome-wide association analyses of 395 women from 8 countries to identify genetic regions associated with 19 different HMO. Our data support FUT2 as the most significantly associated (P < 4.23-9 to P < 4.5-70) gene with seven HMO and provide evidence of balancing selection for FUT2. Although polymorphisms in FUT3 were also associated with variation in lacto-N-fucopentaose II and difucosyllacto-N-tetrose, we found little evidence of selection on FUT3. To our knowledge, this is the first report of the use of genome-wide association analyses on HMO.

Feasibility of the vaccine development for SARS-CoV-2 and other viruses using the shell disorder analysis.

Several related viral shell disorder (disorder of shell proteins of viruses) models were built using a disorder predictor via AI. The parent model detected the presence of high levels of disorder at the outer shell in viruses, for which vaccines are not available. Another model found correlations between inner shell disorder and viral virulence. A third model was able to positively correlate the levels of respiratory transmission of coronaviruses (CoVs). These models are linked together by the fact that they have uncovered two novel immune evading strategies employed by the various viruses. The first involve the use of highly disordered "shape-shifting" outer shell to prevent antibodies from binding tightly to the virus thus leading to vaccine failure. The second usually involves a more disordered inner shell that provides for more efficient binding in the rapid replication of viral particles before any host immune response. This "Trojan horse" immune evasion often backfires on the virus, when the viral load becomes too great at a vital organ, which leads to death of the host. Just as such virulence entails the viral load to exceed at a vital organ, a minimal viral load in the saliva/mucus is necessary for respiratory transmission to be feasible. As for the SARS-CoV-2, no high levels of disorder can be detected at the outer shell membrane (M) protein, but some evidence of correlation between virulence and inner shell (nucleocapsid, N) disorder has been observed. This suggests that not only the development of vaccine for SARS-CoV-2, unlike HIV, HSV and HCV, is feasible but its attenuated vaccine strain can either be found in nature or generated by genetically modifying N.

A Novel Strategy for the Development of Vaccines for SARS-CoV-2 (COVID-19) and Other Viruses Using AI and Viral Shell Disorder.

A model that predicts levels of coronavirus (CoV) respiratory and fecal-oral transmission potentials based on the shell disorder has been built using neural network (artificial intelligence, AI) analysis of the percentage of disorder (PID) in the nucleocapsid, N, and membrane, M, proteins of the inner and outer viral shells, respectively. Using primarily the PID of N, SARS-CoV-2 is grouped as having intermediate levels of both respiratory and fecal-oral transmission potentials. Related studies, using similar methodologies, have found strong positive correlations between virulence and inner shell disorder among numerous viruses, including Nipah, Ebola, and Dengue viruses. There is some evidence that this is also true for SARS-CoV-2 and SARS-CoV, which have N PIDs of 48% and 50%, and case-fatality rates of 0.5-5% and 10.9%, respectively. The underlying relationship between virulence and respiratory potentials has to do with the viral loads of vital organs and body fluids, respectively. Viruses can spread by respiratory means only if the viral loads in saliva and mucus exceed certain minima. Similarly, a patient is likelier to die when the viral load overwhelms vital organs. Greater disorder in inner shell proteins has been known to play important roles in the rapid replication of viruses by enhancing the efficiency pertaining to protein-protein/DNA/RNA/lipid bindings. This paper suggests a novel strategy in attenuating viruses involving comparison of disorder patterns of inner shells (N) of related viruses to identify residues and regions that could be ideal for mutation. The M protein of SARS-CoV-2 has one of the lowest M PID values (6%) in its family, and therefore, this virus has one of the hardest outer shells, which makes it resistant to antimicrobial enzymes in body fluid. While this is likely responsible for its greater contagiousness, the risks of creating an attenuated virus with a more disordered M are discussed.

Shell Disorder Analysis Suggests That Pangolins Offered a Window for a Silent Spread of an Attenuated SARS-CoV-2 Precursor among Humans.

A model to predict the relative levels of respiratory and fecal-oral transmission potentials of coronaviruses (CoVs) by measuring the percentage of protein intrinsic disorder (PID) of the M (Membrane) and N (Nucleoprotein) proteins in their outer and inner shells, respectively, was built before the MERS-CoV outbreak. With MPID = 8.6% and NPID = 50.2%, the 2003 SARS-CoV falls into group B, which consists of CoVs with intermediate levels of both fecal-oral and respiratory transmission potentials. Further validation of the model came with MERS-CoV (MPID = 9%, NPID = 44%) and SARS-CoV-2 (MPID = 5.5%, NPID = 48%) falling into the groups C and B, respectively. Group C contains CoVs with higher fecal-oral but lower respiratory transmission potentials. Unlike SARS-CoV, SARS-CoV-2 with MPID = 5.5% has one of the hardest outer shells among CoVs. Because the hard shell is able to resist the antimicrobial enzymes in body fluids, the infected person is able to shed large quantities of viral particles via saliva and mucus, which could account for the higher contagiousness of SARS-COV-2. Further searches have found that high rigidity of the outer shell is characteristic for the CoVs of burrowing animals, such as rabbits (MPID = 5.6%) and pangolins (MPID = 5-6%), which are in contact with the buried feces. A closer inspection of pangolin-CoVs from 2017 to 2019 reveals that pangolins provided a unique window of opportunity for the entry of an attenuated SARS-CoV-2 precursor into the human population in 2017 or earlier, with the subsequent slow and silent spread as a mild cold that followed by its mutations into the current more virulent form. Evidence of this lies in both the genetic proximity of the pangolin-CoVs to SARS-CoV-2 (∼90%) and differences in N disorder. A 2017 pangolin-CoV strain shows evidence of higher levels of attenuation and higher fecal-oral transmission associated with lower human infectivity via having lower NPID (44.8%). Our shell disorder model predicts this to be a SARS-CoV-2 vaccine strain, as lower inner shell disorder is associated with the lesser virulence in a variety of viruses.

Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids.

The coronavirus (CoV) family consists of viruses that infects a variety of animals including humans with various levels of respiratory and fecal-oral transmission levels depending on the behavior of the viruses' natural hosts and optimal viral fitness. A model to classify and predict the levels of respective respiratory and fecal-oral transmission potentials of the various viruses was built before the outbreak of MERS-CoV using AI and empirically-based molecular tools to predict the disorder level of proteins. Using the percentages of intrinsic disorder (PID) of the nucleocapsid (N) and membrane (M) proteins of CoV, the model easily clustered the viruses into three groups with the SARS-CoV (M PID = 8%, N PID = 50%) falling into Category B, in which viruses have intermediate levels of both respiratory and fecal-oral transmission potentials. Later, MERS-CoV (M PID = 9%, N PID = 44%) was found to be in Category C, which consists of viruses with lower respiratory transmission potential but with higher fecal-oral transmission capabilities. Based on the peculiarities of disorder distribution, the SARS-CoV-2 (M PID = 6%, N PID = 48%) has to be placed in Category B. Our data show however, that the SARS-CoV-2 is very strange with one of the hardest protective outer shell, (M PID = 6%) among coronaviruses. This means that it might be expected to be highly resilient in saliva or other body fluids and outside the body. An infected body is likelier to shed greater numbers of viral particles since the latter is more resistant to antimicrobial enzymes in body fluids. These particles are also likelier to remain active longer. These factors could account for the greater contagiousness of the SARS-CoV-2 and have implications for efforts to prevent its spread.

The skin microbiome facilitates adaptive tetrodotoxin production in poisonous newts.

Rough-skinned newts (Taricha granulosa) use tetrodotoxin (TTX) to block voltage-gated sodium (Nav) channels as a chemical defense against predation. Interestingly, newts exhibit extreme population-level variation in toxicity attributed to a coevolutionary arms race with TTX-resistant predatory snakes, but the source of TTX in newts is unknown. Here, we investigated whether symbiotic bacteria isolated from toxic newts could produce TTX. We characterized the skin-associated microbiota from a toxic and non-toxic population of newts and established pure cultures of isolated bacterial symbionts from toxic newts. We then screened bacterial culture media for TTX using LC-MS/MS and identified TTX-producing bacterial strains from four genera, including Aeromonas, Pseudomonas, Shewanella, and Sphingopyxis. Additionally, we sequenced the Nav channel gene family in toxic newts and found that newts expressed Nav channels with modified TTX binding sites, conferring extreme physiological resistance to TTX. This study highlights the complex interactions among adaptive physiology, animal-bacterial symbiosis, and ecological context.

Rough-skinned newts produce tetrodotoxin or TTX, a deadly neurotoxin that is also present in some pufferfish, octopuses, crabs, starfish, flatworms, frogs, and toads. It remains a mystery why so many different creatures produce this toxin. One possibility is that TTX did not evolve in animals at all, but rather it is made by bacteria living on or in these creatures. In fact, scientists have already shown that TTX-producing bacteria supply pufferfish, octopus, and other animals with the toxin. However, it was not known where TTX in newts and other amphibians comes from. TTX kills animals by blocking specialized ion channels and shutting down the signaling between neurons, but rough-skinned newts appear insensitive to this blockage, making it likely that they have evolved defenses against the toxin. Some garter snakes that feed on these newts have also evolved to become immune to the effects of TTX. If bacteria are the source of TTX in the newts, the emergence of newt-eating snakes resistant to TTX must be putting evolutionary pressure on both the newts and the bacteria to boost their anti-snake defenses. Learning more about these complex relationships will help scientists better understand both evolution and the role of beneficial bacteria. Vaelli et al. have now shown that bacteria living on rough-skinned newts produce TTX. In the experiments, bacteria samples were collected from the skin of the newts and grown in the laboratory. Four different types of bacteria from the samples collected produced TTX. Next, Vaelli et al. looked at five genes that encode the channels normally affected by TTX in newts and found that all them have mutations that prevent them from being blocked by this deadly neurotoxin. This suggests that bacteria living on newts shape the evolution of genes critical to the animals' own survival. Helpful bacteria living on and in animals have important effects on animals' physiology, health, and disease. But understanding these complex interactions is challenging. Rough-skinned newts provide an excellent model system for studying the effects of helpful bacteria living on animals. Vaelli et al. show that a single chemical produced by bacteria can impact diverse aspects of animal biology including physiology, the evolution of their genes, and their interactions with other creatures in their environment.

Corrigendum: What's Normal? Microbiomes in Human Milk and Infant Feces Are Related to Each Other but Vary Geographically: The INSPIRE Study.

[This corrects the article DOI: 10.3389/fnut.2019.00045.].

Rigidity of the Outer Shell Predicted by a Protein Intrinsic Disorder Model Sheds Light on the COVID-19 (Wuhan-2019-nCoV) Infectivity.

The world is currently witnessing an outbreak of a new coronavirus spreading quickly across China and affecting at least 24 other countries. With almost 65,000 infected, a worldwide death toll of at least 1370 (as of 14 February 2020), and with the potential to affect up to two-thirds of the world population, COVID-19 is considered by the World Health Organization (WHO) to be a global health emergency. The speed of spread and infectivity of COVID-19 (also known as Wuhan-2019-nCoV) are dramatically exceeding those of the Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus (SARS-CoV). In fact, since September 2012, the WHO has been notified of 2494 laboratory-confirmed cases of infection with MERS-CoV, whereas the 2002-2003 epidemic of SARS affected 26 countries and resulted in more than 8000 cases. Therefore, although SARS, MERS, and COVID-19 are all the result of coronaviral infections, the causes of the coronaviruses differ dramatically in their transmissibility. It is likely that these differences in infectivity of coronaviruses can be attributed to the differences in the rigidity of their shells which can be evaluated using computational tools for predicting intrinsic disorder predisposition of the corresponding viral proteins.

Nipah shell disorder, modes of infection, and virulence.

The Nipah Virus (NiV) was first isolated during a 1998-9 outbreak in Malaysia. The outbreak initially infected farm pigs and then moved to humans from pigs with a case-fatality rate (CFR) of about 40%. After 2001, regular outbreaks occurred with higher CFRs (~71%, 2001-5, ~93%, 2008-12). The spread arose from drinking virus-laden palm date sap and human-to-human transmission. Intrinsic disorder analysis revealed strong correlation between the percentage of disorder in the N protein and CFR (Regression: r2 = 0.93, p < 0.01, ANOVA: p < 0.01). Distinct disorder and, therefore, genetic differences can be found in all three group of strains. The fact that the transmission modes of the Malaysia strain are different from those of the Bangladesh strains suggests that the correlations may also be linked to the modes of viral transmission. Analysis of the NiV and related viruses suggests links between modes of transmission and disorder of not just the N protein but, also, of M shell protein. The links among shell disorder, transmission modes, and virulence suggest mechanisms by which viruses are attenuated as they passed through different cell hosts from different animal species. These have implications for development of vaccines and epidemiological molecular analytical tools to contain outbreaks.

Multipathogen Analysis of IgA and IgG Antigen Specificity for Selected Pathogens in Milk Produced by Women From Diverse Geographical Regions: The INSPIRE Study.

Breastfeeding provides defense against infectious disease during early life. The mechanisms underlying this protection are complex but likely include the vast array of immune cells and components, such as immunoglobulins, in milk. Simply characterizing the concentrations of these bioactives, however, provides only limited information regarding their potential relationships with disease risk in the recipient infant. Rather, understanding pathogen and antigen specificity profiles of milk-borne immunoglobulins might lead to a more complete understanding of how maternal immunity impacts infant health and wellbeing. Milk produced by women living in 11 geographically dispersed populations was applied to a protein microarray containing antigens from 16 pathogens, including diarrheagenic E. coli, Shigella spp., Salmonella enterica serovar Typhi, Staphylococcus aureus, Streptococcus pneumoniae, Mycobacterium tuberculosis and other pathogens of global health concern, and specific IgA and IgG binding was measured. Our analysis identified novel disease-specific antigen responses and suggests that some IgA and IgG responses vary substantially within and among populations. Patterns of antibody reactivity analyzed by principal component analysis and differential reactivity analysis were associated with either lower-to-middle-income countries (LMICs) or high-income countries (HICs). Antibody levels were generally higher in LMICs than HICs, particularly for Shigella and diarrheagenic E. coli antigens, although sets of S. aureus, S. pneumoniae, and some M. tuberculosis antigens were more reactive in HICs. Differential responses were typically specific to canonical immunodominant antigens, but a set of nondifferential but highly reactive antibodies were specific to antigens possibly universally recognized by antibodies in human milk. This approach provides a promising means to understand how breastfeeding and human milk protect (or do not protect) infants from environmentally relevant pathogens. Furthermore, this approach might lead to interventions to boost population-specific immunity in at-risk breastfeeding mothers and their infants.

Zika and Flavivirus Shell Disorder: Virulence and Fetal Morbidity.

Zika virus (ZIKV) was first discovered in 1947 in Africa. Since then, sporadic ZIKV infections of humans have been reported in Africa and Asia. For a long time, this virus was mostly unnoticed due to its mild symptoms and low fatality rates. However, during the 2015-2016 epidemic in Central and South America, when millions of people were infected, it was discovered that ZIKV causes microcephaly in the babies of mothers infected during pregnancy. An examination of the M and C proteins of the ZIKV shell using the disorder predictor PONDR VLXT revealed that the M protein contains relatively high disorder levels comparable only to those of the yellow fever virus (YFV). On the other hand, the disorder levels in the C protein are relatively low, which can account for the low case fatality rate (CFR) of this virus in contrast to the more virulent YFV, which is characterized by high disorder in its C protein. A larger variation was found in the percentage of intrinsic disorder (PID) in the C protein of various ZIKV strains. Strains of African lineage are characterized by higher PIDs. Using both in vivo and in vitro experiments, laboratories have also previously shown that strains of African origin have a greater potential to inflict higher fetal morbidity than do strains of Asian lineage, with dengue-2 virus (DENV-2) having the least potential. Strong correlations were found between the potential to inflict fetal morbidity and shell disorder in ZIKV (r2 = 0.9) and DENV-2 (DENV-2 + ZIKV, r2 = 0.8). A strong correlation between CFR and PID was also observed when ZIKV was included in an analysis of sets of shell proteins from a variety of flaviviruses (r2 = 0.8). These observations have potential implications for antiviral vaccine development and for the design of cancer therapeutics in terms of developing therapeutic viruses that penetrate hard-to-reach organs.