OBJECTIVES:

To test the hypotheses that minority children with long-bone fractures are less likely to (1) receive analgesics, (2) receive opioid analgesics, and (3) achieve pain reduction.

BACKGROUND AND OBJECTIVES:

A previous single-county study found that retail stores usually asked young-looking tobacco customers to show proof-of-age identification, but a large proportion of illegal tobacco sales to minors occurred after the customers had shown identification proving they were too young to purchase tobacco. We sought to investigate these findings on a larger scale.

BACKGROUND:

Medicaid plays a critical role during the perinatal period, but pregnancy-related Medicaid eligibility only extends for 60 days post partum. In 2014, the Affordable Care Act’s (ACA’s) Medicaid expansions increased adult Medicaid eligibility to 138% of the federal poverty level in participating states, allowing eligible new mothers to remain covered after pregnancy-related coverage expires. We investigate the impact of ACA Medicaid expansions on insurance coverage among new mothers living in poverty.

Cystinuria is an autosomal recessive disorder characterized by excessive urinary excretion of cystine, resulting in recurrent cystine kidney stones, often presenting in childhood. Current treatment options for cystinuria include dietary and/or fluid measures and potassium citrate to reduce cystine excretion and/or increase solubility. Tiopronin and D-penicillamine are used in refractory cases to bind cystine in urine, albeit with serious side effects. A recent study revealed efficacy of nutritional supplement α-lipoic acid (ALA) treatment in preventing kidney stones in a mouse model of cystinuria. Here, we report 2 pediatric patients (6 and 15 years old) with cystinuria who received regular doses of ALA in addition to conventional therapy with potassium citrate. Both patients tolerated ALA without any adverse effects and had reduced frequency of symptomatic and asymptomatic kidney stones with disappearance of existing kidney stones in 1 patient after 2 months of ALA therapy. ALA treatment markedly improved laboratory markers of cystine solubility in urine with increased cystine capacity (–223 to –1 mg/L in patient 1 and +140 to +272 mg/L in patient 2) and decreased cystine supersaturation (1.7 to 0.88 in patient 1 and 0.64 to 0.48 in patient 2) without any changes in cystine excretion or urine pH. Our findings suggest that ALA improves solubility of cystine in urine and prevents stone formation in patients with cystinuria who do not respond to diet and citrate therapy.

OBJECTIVES:

In this study, we evaluate the efficacy of Families Talking Together (FTT), a triadic intervention to reduce adolescent sexual risk behavior.

OBJECTIVES:

To describe (1) the developmental trajectories of peer victimization from 6 to 17 years of age and (2) the early childhood behaviors and family characteristics associated with the trajectories.

Systemic sclerosis sine scleroderma (ssSSc) is a rare variant of systemic sclerosis, with only one pediatric case reported in the medical literature to date. Pulmonary arterial hypertension as the presenting feature of ssSSc is extremely rare, even in adults, and so far has never been reported in children. We report, for the first time, a case of pediatric ssSSc in a 3-year-old girl, who presented with interstitial lung disease and pulmonary hypertension. The patient was prescribed early aggressive pulmonary vasodilators combined with anti-inflammatory medications. The clinical response was good, and her current condition at 12 years of age is remarkable, considering the high mortality rates reported in adults. We underscore the importance of early aggressive treatment in future cases of similar presentation.

BACKGROUND:

Several studies have investigated the association of breastfeeding status with offspring mortality in Africa, but most studies were from one center only or had limited statistical power to draw robust conclusions.

OBJECTIVES:

Standing orders are an effective way to increase vaccination rates, yet little is known about how pediatricians use this strategy for childhood immunizations. We assessed current use of, barriers to using, and factors associated with use of standing orders for vaccination among pediatricians.

BACKGROUND:

There is a dearth of evidence regarding the association of use of electronic cigarettes (e-cigarettes) with certain product characteristics and adolescent and young adult risk of unhealthy tobacco use patterns (eg, frequency of combustible cigarette smoking), which is needed to inform the regulation of e-cigarettes.

As the technical ability for genetic diagnosis continues to improve, an increasing number of diagnoses are made in infancy or as early as the neonatal period. Many of these diagnoses are known to be associated with developmental delay and intellectual disability, features that would not be clinically detectable at the time of diagnosis. Others may be associated with cognitive impairment, but the incidence and severity are yet to be fully described. These neonates and infants with genetic diagnoses therefore represent an emerging group of patients who are at high risk for neurodevelopmental disabilities. Although there are well-established developmental supports for high-risk infants, particularly preterm infants, after discharge from the NICU, programs specifically for infants with genetic diagnoses are rare. And although previous research has demonstrated the positive effect of early developmental interventions on outcomes among preterm infants, the impact of such supports for infants with genetic disorders who may be born term, remains to be understood. We therefore review the literature regarding existing developmental assessment and intervention approaches for children with genetic disorders, evaluating these in the context of current developmental supports postdischarge for preterm infants. Further research into the role of developmental support programs for early assessment and intervention in high-risk neonates diagnosed with rare genetic disorders is needed.

Multienvironment trials (METs) are widely used to assess the performance of promising crop germplasm. Though seldom designed to elucidate genetic mechanisms, MET data sets are often much larger than could be duplicated for genetic research and, given proper interpretation, may offer valuable insights into the genetics of adaptation across time and space. The Cooperative Dry Bean Nursery (CDBN) is a MET for common bean (Phaseolus vulgaris) grown for > 70 years in the United States and Canada, consisting of 20–50 entries each year at 10–20 locations. The CDBN provides a rich source of phenotypic data across entries, years, and locations that is amenable to genetic analysis. To study stable genetic effects segregating in this MET, we conducted genome-wide association studies (GWAS) using best linear unbiased predictions derived across years and locations for 21 CDBN phenotypes and genotypic data (1.2 million SNPs) for 327 CDBN genotypes. The value of this approach was confirmed by the discovery of three candidate genes and genomic regions previously identified in balanced GWAS. Multivariate adaptive shrinkage (mash) analysis, which increased our power to detect significant correlated effects, found significant effects for all phenotypes. Mash found two large genomic regions with effects on multiple phenotypes, supporting a hypothesis of pleiotropic or linked effects that were likely selected on in pursuit of a crop ideotype. Overall, our results demonstrate that statistical genomics approaches can be used on MET phenotypic data to discover significant genetic effects and to define genomic regions associated with crop improvement.

In plant–pathogen relations, disease symptoms arise from the interaction of the host and pathogen genomes. Host–pathogen functional gene interactions are well described, whereas little is known about how the pathogen genetic variation modulates both organisms’ transcriptomes. To model and generate hypotheses on a generalist pathogen control of gene expression regulation, we used the Arabidopsis thaliana–Botrytis cinerea pathosystem and the genetic diversity of a collection of 96 B. cinerea isolates. We performed expression-based genome-wide association (eGWA) for each of 23,947 measurable transcripts in Arabidopsis (host), and 9267 measurable transcripts in B. cinerea (pathogen). Unlike other eGWA studies, we detected a relative absence of locally acting expression quantitative trait loci (cis-eQTL), partly caused by structural variants and allelic heterogeneity hindering their identification. This study identified several distantly acting trans-eQTL linked to eQTL hotspots dispersed across Botrytis genome that altered only Botrytis transcripts, only Arabidopsis transcripts, or transcripts from both species. Gene membership in the trans-eQTL hotspots suggests links between gene expression regulation and both known and novel virulence mechanisms in this pathosystem. Genes annotated to these hotspots provide potential targets for blocking manipulation of the host response by this ubiquitous generalist necrotrophic pathogen.

Secondary branch number per panicle plays a crucial role in regulating grain number and yield in rice. Here, we report the positional cloning and functional characterization for SECONDARY BRANCH NUMBER7 (qSBN7), a quantitative trait locus affecting secondary branch per panicle and grain number. Our research revealed that the causative variants of qSBN7 are located in the distal promoter region of FRIZZLE PANICLE (FZP), a gene previously associated with the repression of axillary meristem development in rice spikelets. qSBN7 is a novel allele of FZP that causes an ~56% decrease in its transcriptional level, leading to increased secondary branch and grain number, and reduced grain length. Field evaluations showed that qSBN7 increased grain yield by 10.9% in a temperate japonica variety, TN13, likely due to its positive effect on sink capacity. Our findings suggest that incorporation of qSBN7 can increase yield potential and improve the breeding of elite rice varieties.

Many complex human traits exhibit differences between sexes. While numerous factors likely contribute to this phenomenon, growing evidence from genome-wide studies suggest a partial explanation: that males and females from the same population possess differing genetic architectures. Despite this, mapping gene-by-sex (GxS) interactions remains a challenge likely because the magnitude of such an interaction is typically and exceedingly small; traditional genome-wide association techniques may be underpowered to detect such events, due partly to the burden of multiple test correction. Here, we developed a local Bayesian regression (LBR) method to estimate sex-specific SNP marker effects after fully accounting for local linkage-disequilibrium (LD) patterns. This enabled us to infer sex-specific effects and GxS interactions either at the single SNP level, or by aggregating the effects of multiple SNPs to make inferences at the level of small LD-based regions. Using simulations in which there was imperfect LD between SNPs and causal variants, we showed that aggregating sex-specific marker effects with LBR provides improved power and resolution to detect GxS interactions over traditional single-SNP-based tests. When using LBR to analyze traits from the UK Biobank, we detected a relatively large GxS interaction impacting bone mineral density within ABO, and replicated many previously detected large-magnitude GxS interactions impacting waist-to-hip ratio. We also discovered many new GxS interactions impacting such traits as height and body mass index (BMI) within regions of the genome where both male- and female-specific effects explain a small proportion of phenotypic variance (R² < 1 x 10^–4), but are enriched in known expression quantitative trait loci.

Single-cross hybrids have been critical to the improvement of maize (Zea mays L.), but the characterization of their genetic architectures remains challenging. Previous studies of hybrid maize have shown the contribution of within-locus complementation effects (dominance) and their differential importance across functional classes of loci. However, they have generally considered panels of limited genetic diversity, and have shown little benefit from genomic prediction based on dominance or functional enrichments. This study investigates the relevance of dominance and functional classes of variants in genomic models for agronomic traits in diverse populations of hybrid maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the U.S. (1106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1640 hybrids). We investigated three agronomic traits: days to silking (DTS), plant height (PH), and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results suggest that dominance and gene annotations improve genomic prediction across diverse populations in hybrid maize.

Real geography is continuous, but standard models in population genetics are based on discrete, well-mixed populations. As a result, many methods of analyzing genetic data assume that samples are a random draw from a well-mixed population, but are applied to clustered samples from populations that are structured clinally over space. Here, we use simulations of populations living in continuous geography to study the impacts of dispersal and sampling strategy on population genetic summary statistics, demographic inference, and genome-wide association studies (GWAS). We find that most common summary statistics have distributions that differ substantially from those seen in well-mixed populations, especially when Wright’s neighborhood size is < 100 and sampling is spatially clustered. "Stepping-stone" models reproduce some of these effects, but discretizing the landscape introduces artifacts that in some cases are exacerbated at higher resolutions. The combination of low dispersal and clustered sampling causes demographic inference from the site frequency spectrum to infer more turbulent demographic histories, but averaged results across multiple simulations revealed surprisingly little systematic bias. We also show that the combination of spatially autocorrelated environments and limited dispersal causes GWAS to identify spurious signals of genetic association with purely environmentally determined phenotypes, and that this bias is only partially corrected by regressing out principal components of ancestry. Last, we discuss the relevance of our simulation results for inference from genetic variation in real organisms.

The question of the relative evolutionary roles of adaptive and nonadaptive processes has been a central debate in population genetics for nearly a century. While advances have been made in the theoretical development of the underlying models, and statistical methods for estimating their parameters from large-scale genomic data, a framework for an appropriate null model remains elusive. A model incorporating evolutionary processes known to be in constant operation, genetic drift (as modulated by the demographic history of the population) and purifying selection, is lacking. Without such a null model, the role of adaptive processes in shaping within- and between-population variation may not be accurately assessed. Here, we investigate how population size changes and the strength of purifying selection affect patterns of variation at "neutral" sites near functional genomic components. We propose a novel statistical framework for jointly inferring the contribution of the relevant selective and demographic parameters. By means of extensive performance analyses, we quantify the utility of the approach, identify the most important statistics for parameter estimation, and compare the results with existing methods. Finally, we reanalyze genome-wide population-level data from a Zambian population of Drosophila melanogaster, and find that it has experienced a much slower rate of population growth than was inferred when the effects of purifying selection were neglected. Our approach represents an appropriate null model, against which the effects of positive selection can be assessed.

Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term and to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.

The vertebrate limb serves as an experimental paradigm to study mechanisms that regulate development of the stereotypical skeletal elements. In this study, we simultaneously inactivated Sall4 using Hoxb6Cre and Plzf in mouse embryos, and found that their combined function regulates development of the proximal-anterior skeletal elements in hindlimbs. The Sall4; Plzf double knockout exhibits severe defects in the femur, tibia, and anterior digits, distinct defects compared to other allelic series of Sall4; Plzf. We found that Sall4 regulates Plzf expression prior to hindlimb outgrowth. Further expression analysis indicated that Hox10 genes and GLI3 are severely downregulated in the Sall4; Plzf double knockout hindlimb bud. In contrast, PLZF expression is reduced but detectable in Sall4; Gli3 double knockout limb buds, and SALL4 is expressed in the Plzf; Gli3 double knockout limb buds. These results indicate that Plzf, Gli3, and Hox10 genes downstream of Sall4, regulate femur and tibia development. In the autopod, we show that Sall4 negatively regulates Hedgehog signaling, which allows for development of the most anterior digit. Collectively, our study illustrates genetic systems that regulate development of the proximal-anterior skeletal elements in hindlimbs.

The Hippo pathway is an evolutionarily conserved signaling network that regulates organ size, cell fate, and tumorigenesis. In the context of organ size control, the pathway incorporates a large variety of cellular cues, such as cell polarity and adhesion, into an integrated transcriptional response. The central Hippo signaling effector is the transcriptional coactivator Yorkie, which controls gene expression in partnership with different transcription factors, most notably Scalloped. When it is not activated by Yorkie, Scalloped can act as a repressor of transcription, at least in part due to its interaction with the corepressor protein Tgi. The mechanism by which Tgi represses transcription is incompletely understood, and therefore we sought to identify proteins that potentially operate together with Tgi. Using an affinity purification and mass-spectrometry approach we identified Pits and CtBP as Tgi-interacting proteins, both of which have been linked to transcriptional repression. Both Pits and CtBP were required for Tgi to suppress the growth of the Drosophila melanogaster eye and CtBP loss suppressed the undergrowth of yorkie mutant eye tissue. Furthermore, as reported previously for Tgi, overexpression of Pits repressed transcription of Hippo pathway target genes. These findings suggest that Tgi might operate together with Pits and CtBP to repress transcription of genes that normally promote tissue growth. The human orthologs of Tgi, CtBP, and Pits (VGLL4, CTBP2, and IRF2BP2) have previously been shown to physically and functionally interact to control transcription, implying that the mechanism by which these proteins control transcriptional repression is conserved throughout evolution.

Repeated alcohol experiences can produce long-lasting memories for sensory cues associated with intoxication. These memories can problematically trigger relapse in individuals recovering from alcohol use disorder (AUD). The molecular mechanisms by which ethanol changes memories to become long-lasting and inflexible remain unclear. New methods to analyze gene expression within precise neuronal cell types can provide further insight toward AUD prevention and treatment. Here, we used genetic tools in Drosophila melanogaster to investigate the lasting consequences of ethanol on transcription in memory-encoding neurons. Drosophila rely on mushroom body (MB) neurons to make associative memories, including memories of ethanol-associated sensory cues. Differential expression analyses revealed that distinct transcripts, but not genes, in the MB were associated with experiencing ethanol alone compared to forming a memory of an odor cue associated with ethanol. Adult MB-specific knockdown of spliceosome-associated proteins demonstrated the necessity of RNA-processing in ethanol memory formation. These findings highlight the dynamic, context-specific regulation of transcription in cue-encoding neurons, and the lasting effect of ethanol on transcript usage during memory formation.

BEAF (Boundary Element-Associated Factor) was originally identified as a Drosophila melanogaster chromatin domain insulator-binding protein, suggesting a role in gene regulation through chromatin organization and dynamics. Genome-wide mapping found that BEAF usually binds near transcription start sites, often of housekeeping genes, suggesting a role in promoter function. This would be a nontraditional role for an insulator-binding protein. To gain insight into molecular mechanisms of BEAF function, we identified interacting proteins using yeast two-hybrid assays. Here, we focus on the transcription factor Serendipity (Sry-). Interactions were confirmed in pull-down experiments using bacterially expressed proteins, by bimolecular fluorescence complementation, and in a genetic assay in transgenic flies. Sry- interacted with promoter-proximal BEAF both when bound to DNA adjacent to BEAF or > 2-kb upstream to activate a reporter gene in transient transfection experiments. The interaction between BEAF and Sry- was detected using both a minimal developmental promoter (y) and a housekeeping promoter (RpS12), while BEAF alone strongly activated the housekeeping promoter. These two functions for BEAF implicate it in playing a direct role in gene regulation at hundreds of BEAF-associated promoters.

Replication initiation in eukaryotic cells occurs asynchronously throughout S phase, yielding early- and late-replicating regions of the genome, a process known as replication timing (RT). RT changes during development to ensure accurate genome duplication and maintain genome stability. To understand the relative contributions that cell lineage, cell cycle, and replication initiation regulators have on RT, we utilized the powerful developmental systems available in Drosophila melanogaster. We generated and compared RT profiles from mitotic cells of different tissues and from mitotic and endocycling cells of the same tissue. Our results demonstrate that cell lineage has the largest effect on RT, whereas switching from a mitotic to an endoreplicative cell cycle has little to no effect on RT. Additionally, we demonstrate that the RT differences we observed in all cases are largely independent of transcriptional differences. We also employed a genetic approach in these same cell types to understand the relative contribution the eukaryotic RT control factor, Rif1, has on RT control. Our results demonstrate that Rif1 can function in a tissue-specific manner to control RT. Importantly, the Protein Phosphatase 1 (PP1) binding motif of Rif1 is essential for Rif1 to regulate RT. Together, our data support a model in which the RT program is primarily driven by cell lineage and is further refined by Rif1/PP1 to ultimately generate tissue-specific RT programs.

During meiotic prophase, concurrent transcription, recombination, and chromosome synapsis place substantial topological strain on chromosomal DNA, but the role of topoisomerases in this context remains poorly defined. Here, we analyzed the roles of topoisomerases I and II (Top1 and Top2) during meiotic prophase in Saccharomyces cerevisiae. We show that both topoisomerases accumulate primarily in promoter-containing intergenic regions of actively transcribing genes, including many meiotic double-strand break (DSB) hotspots. Despite the comparable binding patterns, top1 and top2 mutations have different effects on meiotic recombination. TOP1 disruption delays DSB induction and shortens the window of DSB accumulation by an unknown mechanism. By contrast, temperature-sensitive top2-1 mutants exhibit a marked delay in meiotic chromosome remodeling and elevated DSB signals on synapsed chromosomes. The problems in chromosome remodeling were linked to altered Top2 binding patterns rather than a loss of Top2 catalytic activity, and stemmed from a defect in recruiting the chromosome remodeler Pch2/TRIP13 to synapsed chromosomes. No chromosomal defects were observed in the absence of TOP1. Our results imply independent roles for Top1 and Top2 in modulating meiotic chromosome structure and recombination.

Age-at-onset is one of the critical traits in cohort studies of age-related diseases. Large-scale genome-wide association studies (GWAS) of age-at-onset traits can provide more insights into genetic effects on disease progression and transitions between stages. Moreover, proportional hazards (or Cox) regression models can achieve higher statistical power in a cohort study than a case-control trait using logistic regression. Although mixed-effects models are widely used in GWAS to correct for sample dependence, application of Cox mixed-effects models (CMEMs) to large-scale GWAS is so far hindered by intractable computational cost. In this work, we propose COXMEG, an efficient R package for conducting GWAS of age-at-onset traits using CMEMs. COXMEG introduces fast estimation algorithms for general sparse relatedness matrices including, but not limited to, block-diagonal pedigree-based matrices. COXMEG also introduces a fast and powerful score test for dense relatedness matrices, accounting for both population stratification and family structure. In addition, COXMEG generalizes existing algorithms to support positive semidefinite relatedness matrices, which are common in twin and family studies. Our simulation studies suggest that COXMEG, depending on the structure of the relatedness matrix, is orders of magnitude computationally more efficient than coxme and coxph with frailty for GWAS. We found that using sparse approximation of relatedness matrices yielded highly comparable results in controlling false-positive rate and retaining statistical power for an ethnically homogeneous family-based sample. By applying COXMEG to a study of Alzheimer’s disease (AD) with a Late-Onset Alzheimer’s Disease Family Study from the National Institute on Aging sample comprising 3456 non-Hispanic whites and 287 African Americans, we identified the APOE 4 variant with strong statistical power (P = 1e–101), far more significant than that reported in a previous study using a transformed variable and a marginal Cox model. Furthermore, we identified novel SNP rs36051450 (P = 2e–9) near GRAMD1B, the minor allele of which significantly reduced the hazards of AD in both genders. These results demonstrated that COXMEG greatly facilitates the application of CMEMs in GWAS of age-at-onset traits.

There is increasing interest in developing diagnostics that discriminate individual mutagenic mechanisms in a range of applications that include identifying population-specific mutagenesis and resolving distinct mutation signatures in cancer samples. Analyses for these applications assume that mutagenic mechanisms have a distinct relationship with neighboring bases that allows them to be distinguished. Direct support for this assumption is limited to a small number of simple cases, e.g., CpG hypermutability. We have evaluated whether the mechanistic origin of a point mutation can be resolved using only sequence context for a more complicated case. We contrasted single nucleotide variants originating from the multitude of mutagenic processes that normally operate in the mouse germline with those induced by the potent mutagen N-ethyl-N-nitrosourea (ENU). The considerable overlap in the mutation spectra of these two samples make this a challenging problem. Employing a new, robust log-linear modeling method, we demonstrate that neighboring bases contain information regarding point mutation direction that differs between the ENU-induced and spontaneous mutation variant classes. A logistic regression classifier exhibited strong performance at discriminating between the different mutation classes. Concordance between the feature set of the best classifier and information content analyses suggest our results can be generalized to other mutation classification problems. We conclude that machine learning can be used to build a practical classification tool to identify the mutation mechanism for individual genetic variants. Software implementing our approach is freely available under an open-source license.

Phenotypic plasticity is defined as the property of organisms to produce distinct phenotypes in response to environmental variation. While for more than a century, biologists have proposed this organismal feature to play an important role in evolution and the origin of novelty, the idea has remained contentious. Plasticity is found in all domains of life, but only recently has there been an increase in empirical studies. This contribution is intended as a fresh view and will discuss current and future challenges of plasticity research, and the need to identify associated molecular mechanisms. After a brief summary of conceptual, theoretical, and historical aspects, some of which were responsible for confusion and contention, I will formulate three major research directions and predictions for the role of plasticity as a facilitator of novelty. These predictions result in a four-step model that, when properly filled with molecular mechanisms, will reveal plasticity as a major factor of evolution. Such mechanistic insight must be complemented with comparative investigations to show that plasticity has indeed created novelty and innovation. Together, such studies will help develop a true developmental evolutionary biology.

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The spirochete Borrelia burgdorferi sensu lato is the causative agent of Lyme disease (LD). The spirochetes produce the CspZ protein that binds to a complement regulator, factor H (FH). Such binding downregulates activation of host complement to facilitate spirochete evasion of complement killing. However, vaccination with CspZ does not protect against LD infection. In this study, we demonstrated that immunization with CspZ-YA, a CspZ mutant protein with no FH-binding activity, protected mice from infection by several spirochete genotypes introduced via tick feeding. We found that the sera from CspZ-YA-vaccinated mice more efficiently eliminated spirochetes and blocked CspZ FH-binding activity than sera from CspZ-immunized mice. We also found that vaccination with CspZ, but not CspZ-YA, triggered the production of anti-FH antibodies, justifying CspZ-YA as an LD vaccine candidate. The mechanistic and efficacy information derived from this study provides insights into the development of a CspZ-based LD vaccine.