Traveling Waves and Estimation of Minimal Wave Speed for a Diffusive Influenza Model with Multiple Strains.

Antiviral treatment remains one of the key pharmacological interventions against influenza pandemic. However, widespread use of antiviral drugs brings with it the danger of drug resistance evolution. To assess the risk of the emergence and diffusion of resistance, in this paper, we develop a diffusive influenza model where influenza infection involves both drug-sensitive and drug-resistant strains. We first analyze its corresponding reaction model, whose reproduction numbers and equilibria are derived. The results show that the sensitive strains can be eliminated by treatment. Then, we establish the existence of the three kinds of traveling waves starting from the disease-free equilibrium, i.e., semi-traveling waves, strong traveling waves and persistent traveling waves, from which we can get some useful information (such as whether influenza will spread, asymptotic speed of propagation, the final state of the wavefront). On the other hand, we discuss three situations in which semi-traveling waves do not exist. When the control reproduction number [Formula: see text] is larger than 1, the conditions for the existence and nonexistence of traveling waves are determined completely by the reproduction numbers [Formula: see text], [Formula: see text] and the wave speed c. Meanwhile, we give an interval estimation of minimal wave speed for influenza transmission, which has important guiding significance for the control of influenza in reality. Our findings demonstrate that the control of influenza depends not only on the rates of resistance emergence and transmission during treatment, but also on the diffusion rates of influenza strains, which have been overlooked in previous modeling studies. This suggests that antiviral treatment should be implemented appropriately, and infected individuals (especially with the resistant strain) should be tested and controlled effectively. Finally, we outline some future directions that deserve further investigation.

A Host-Parasite System with Multiple Parasite Strains and Superinfection Revisited: The Global Dynamics.

In this paper, we revisit a host-parasite system with multiple parasite strains and superinfection proposed by Nowak and May (Proc R Soc Lond B 255(1342):81-89, 1994), and study its global dynamics when we relax the two strict conditions assumed therein. As for system with two parasite strains, we derive that the basic reproduction number [Formula: see text] is the threshold condition for parasite extinction and the invasion reproduction number [Formula: see text] is the subthreshold condition for coexistence of two parasite strains. As for system with three parasite strains, we are surprised to discover the global stability of parasite-free and coexistence equilibrium, which is distinct from the previous result. Furthermore, for system with n strains, we obtain the global asymptotical stability of the parasite-free equilibrium, conjecture a general result on the global stability of coexistence equilibrium and provide two numerical examples to testify our conjecture.

Recombinant Receptor-Binding Domains of Multiple Middle East Respiratory Syndrome Coronaviruses (MERS-CoVs) Induce Cross-Neutralizing Antibodies against Divergent Human and Camel MERS-CoVs and Antibody Escape Mutants.

Middle East respiratory syndrome coronavirus (MERS-CoV) binds to cellular receptor dipeptidyl peptidase 4 (DPP4) via the spike (S) protein receptor-binding domain (RBD). The RBD contains critical neutralizing epitopes and serves as an important vaccine target. Since RBD mutations occur in different MERS-CoV isolates and antibody escape mutants, cross-neutralization of divergent MERS-CoV strains by RBD-induced antibodies remains unknown. Here, we constructed four recombinant RBD (rRBD) proteins with single or multiple mutations detected in representative human MERS-CoV strains from the 2012, 2013, 2014, and 2015 outbreaks, respectively, and one rRBD protein with multiple changes derived from camel MERS-CoV strains. Like the RBD of prototype EMC2012 (EMC-RBD), all five RBDs maintained good antigenicity and functionality, the ability to bind RBD-specific neutralizing monoclonal antibodies (MAbs) and the DPP4 receptor, and high immunogenicity, able to elicit S-specific antibodies. They induced potent neutralizing antibodies cross-neutralizing 17 MERS pseudoviruses expressing S proteins of representative human and camel MERS-CoV strains identified during the 2012-2015 outbreaks, 5 MAb escape MERS-CoV mutants, and 2 live human MERS-CoV strains. We then constructed two RBDs mutated in multiple key residues in the receptor-binding motif (RBM) of RBD and demonstrated their strong cross-reactivity with anti-EMC-RBD antibodies. These RBD mutants with diminished DPP4 binding also led to virus attenuation, suggesting that immunoevasion after RBD immunization is accompanied by loss of viral fitness. Therefore, this study demonstrates that MERS-CoV RBD is an important vaccine target able to induce highly potent and broad-spectrum neutralizing antibodies against infection by divergent circulating human and camel MERS-CoV strains. IMPORTANCE: MERS-CoV was first identified in June 2012 and has since spread in humans and camels. Mutations in its spike (S) protein receptor-binding domain (RBD), a key vaccine target, have been identified, raising concerns over the efficacy of RBD-based MERS vaccines against circulating human and camel MERS-CoV strains. Here, we constructed five vaccine candidates, designated 2012-RBD, 2013-RBD, 2014-RBD, 2015-RBD, and Camel-RBD, containing single or multiple mutations in the RBD of representative human and camel MERS-CoV strains during the 2012-2015 outbreaks. These RBD-based vaccine candidates maintained good functionality, antigenicity, and immunogenicity, and they induced strong cross-neutralizing antibodies against infection by divergent pseudotyped and live MERS-CoV strains, as well as antibody escape MERS-CoV mutants. This study provides impetus for further development of a safe, highly effective, and broad-spectrum RBD-based subunit vaccine to prevent MERS-CoV infection.

Identification of Genes that Control Silk Yield by RNA Sequencing Analysis of Silkworm (Bombyx mori) Strains of Variable Silk Yield.

Silk is an important natural fiber of high economic value, and thus genetic study of the silkworm is a major area of research. Transcriptome analysis can provide guidance for genetic studies of silk yield traits. In this study, we performed a transcriptome comparison using multiple silkworms with different silk yields. A total of 22 common differentially expressed genes (DEGs) were identified in multiple strains and were mainly involved in metabolic pathways. Among these, seven significant common DEGs were verified by quantitative reverse transcription polymerase chain reaction, and the results coincided with the findings generated by RNA sequencing. Association analysis showed that BGIBMGA003330 and BGIBMGA005780 are significantly associated with cocoon shell weight and encode uridine nucleosidase and small heat shock protein, respectively. Functional annotation of these genes suggest that these play a role in silkworm silk gland development or silk protein synthesis. In addition, we performed principal component analysis (PCA) in combination with wild silkworm analysis, which indicates that modern breeding has a stronger selection effect on silk yield traits than domestication, and imply that silkworm breeding induces aggregation of genes related to silk yield.

Cytomegalovirus pneumonia of infants in Africa: a narrative literature review.

Cytomegalovirus pneumonia has repeatedly been described in the context of HIV-exposed uninfected and HIV-infected infants. Despite its significant role in the etiology of childhood pneumonia, there is still a paucity of literature generally, and specifically in Africa, suggesting that it might be a neglected disease. Emerging evidence highlights the importance of postnatal transmission through breastmilk. The pathogenetic significance of the multiplicity of strains acquired through repeated re-infections in early infancy is unknown. The development of cheap, accurate diagnostic tools and safe, effective antivirals and the maintenance of effective prevention and treatment of pediatric HIV are needed to manage cytomegalovirus pneumonia in low-resource settings.

Modeling Competitive Mixtures With the Lotka-Volterra Framework for More Complex Fitness Assessment Between Strains.

With increasing resolution of microbial diversity at the genomic level, experimental and modeling frameworks that translate such diversity into phenotypes are highly needed. This is particularly important when comparing drug-resistant with drug-sensitive pathogen strains, when anticipating epidemiological implications of microbial diversity, and when designing control measures. Classical approaches quantify differences between microbial strains using the exponential growth model, and typically report a selection coefficient for the relative fitness differential between two strains. The apparent simplicity of such approaches comes with the costs of limiting the range of biological scenarios that can be captured, and biases strain fitness estimates to polarized extremes of competitive exclusion. Here, we propose a mathematical and statistical framework based on the Lotka-Volterra model, that can capture frequency-dependent competition between microbial strains within-host and upon transmission. As a proof-of-concept, the model is applied to a previously-published dataset from in-vivo competitive mixture experiments with influenza strains in ferrets (McCaw et al., 2011). We show that for the same data, our model predicts a scenario of coexistence between strains, and supports a higher bottleneck size in the range of 35-145 virions transmitted from donor to recipient host. Thanks to its simplicity and generality, such framework could be applied to other ecological scenarios of microbial competition, enabling a more complex and nuanced view of possible outcomes between two strains, beyond competitive exclusion.

Multi-Locus Next-Generation Sequence Typing of DNA Extracted From Pooled Colonies Detects Multiple Unrelated Candida albicans Strains in a Significant Proportion of Patient Samples.

The yeast Candida albicans is an important opportunistic human pathogen. For C. albicans strain typing or drug susceptibility testing, a single colony recovered from a patient sample is normally used. This is insufficient when multiple strains are present at the site sampled. How often this is the case is unclear. Previous studies, confined to oral, vaginal and vulvar samples, have yielded conflicting results and have assessed too small a number of colonies per sample to reliably detect the presence of multiple strains. We developed a next-generation sequencing (NGS) modification of the highly discriminatory C. albicans MLST (multilocus sequence typing) method, 100+1 NGS-MLST, for detection and typing of multiple strains in clinical samples. In 100+1 NGS-MLST, DNA is extracted from a pool of colonies from a patient sample and also from one of the colonies. MLST amplicons from both DNA preparations are analyzed by high-throughput sequencing. Using base call frequencies, our bespoke DALMATIONS software determines the MLST type of the single colony. If base call frequency differences between pool and single colony indicate the presence of an additional strain, the differences are used to computationally infer the second MLST type without the need for MLST of additional individual colonies. In mixes of previously typed pairs of strains, 100+1 NGS-MLST reliably detected a second strain. Inferred MLST types of second strains were always more similar to their real MLST types than to those of any of 59 other isolates (22 of 31 inferred types were identical to the real type). Using 100+1 NGS-MLST we found that 7/60 human samples, including three superficial candidiasis samples, contained two unrelated strains. In addition, at least one sample contained two highly similar variants of the same strain. The probability of samples containing unrelated strains appears to differ considerably between body sites. Our findings indicate the need for wider surveys to determine if, for some types of samples, routine testing for the presence of multiple strains is warranted. 100+1 NGS-MLST is effective for this purpose.

Five challenges in modelling interacting strain dynamics.

Population epidemiological models where hosts can be infected sequentially by different strains have the potential to help us understand many important diseases. Researchers have in recent years started to develop and use such models, but the extra layer of complexity from multiple strains brings with it many technical challenges. It is therefore hard to build models which have realistic assumptions yet are tractable. Here we outline some of the main challenges in this area. First we begin with the fundamental question of how to translate from complex small-scale dynamics within a host to useful population models. Next we consider the nature of so-called "strain space". We describe two key types of host heterogeneities, and explain how models could help generate a better understanding of their effects. Finally, for diseases with many strains, we consider the challenge of modelling how immunity accumulates over multiple exposures.

Strain Variation and Disease Severity in Congenital Cytomegalovirus Infection: In Search of a Viral Marker.

The wide spectrum of congenital cytomegalovirus (CMV) disease and known differences in the biology and in vitro growth of CMV strains continue to drive studies in search for specific viral genetic determinants that may predict severity of congenital CMV disease. Several CMV genes have been studied in detail in congenitally infected children, but the complexity of the viral genome and differences in the definition of symptomatic disease versus asymptomatic CMV infection continue to raise questions related to what constitutes a pathogenic CMV strain.

Multiple strain infections and high genotypic diversity among Mycobacterium avium subsp. paratuberculosis field isolates from diseased wild and domestic ruminant species in the eastern Alpine region of Austria.

Johne's disease, or paratuberculosis, is a chronic fatal ruminant gastroenteritis caused by Mycobacterium avium subspecies paratuberculosis (MAP) whose foodborne zoonotic potential and association with Crohn's disease are still under debate. The disease is widespread but its epidemiology and epizootiology remains elusive. Wildlife is suspected to play a major role. After a surge in MAP seroprevalence in Austrian cattle, paratuberculosis was declared a notifiable disease in Austria in 2006. At the same time a rise in MAP cases in wild ruminant populations in the Austrian province of Styria was reported. All five autochthonous ruminants were affected. Genetic analysis of isolates, yielded numerous genotypes (>15) and several multiple strain infections (15%) across host species. Identical MIRU-VNTR profiles were identified in different species and sampling locations. On the other hand varying MIRU-VNTR profiles were revealed at the same location and in conspecifics. Our data, taken together with earlier epidemiological studies on MAP and other mycobacteria, raised concerns about the organisms' ecology. Constraints regarding in vitro culture of this highly fastidious organism potentially bias our current understanding of its epidemiology. We suggest that MAP infections could be polyclonal and question the informative value of genotyping a single MAP colony derived from a single specimen for epidemiological analysis of MAP.