Asymmetric Cluster-Based Measures for Comparative Phylogenetics.

Phylogenetic inference and reconstruction methods generate hypotheses on evolutionary history. Competing inference methods are frequently used, and the evaluation of the generated hypotheses is achieved using tree comparison costs. The Robinson-Foulds (RF) distance is a widely used cost to compare the topology of two trees, but this cost is sensitive to tree error and can overestimate tree differences. To overcome this limitation, a refined version of the RF distance called the Cluster Affinity (CA) distance was introduced. However, CA distances are symmetric and cannot compare different types of trees. These asymmetric comparisons occur when gene trees are compared with species trees, when disparate datasets are integrated into a supertree, or when tree comparison measures are used to infer a phylogenetic network. In this study, we introduce a relaxation of the original Affinity distance to compare heterogeneous trees called the asymmetric CA cost. We also develop a biologically interpretable cost, the Cluster Support cost that normalizes by cluster size across gene trees. The characteristics of these costs are similar to the symmetric CA cost. We describe efficient algorithms, derive the exact diameters, and use these to standardize the cost to be applicable in practice. These costs provide objective, fine-scale, and biologically interpretable values that can assess differences and similarities between phylogenetic trees.

Reverse-zoonoses of 2009 H1N1 pandemic influenza A viruses and evolution in United States swine results in viruses with zoonotic potential.

The 2009 H1N1 pandemic (pdm09) lineage of influenza A virus (IAV) crosses interspecies barriers with frequent human-to-swine spillovers each year. These spillovers reassort and drift within swine populations, leading to genetically and antigenically novel IAV that represent a zoonotic threat. We quantified interspecies transmission of the pdm09 lineage, persistence in swine, and identified how evolution in swine impacted zoonotic risk. Human and swine pdm09 case counts between 2010 and 2020 were correlated and human pdm09 burden and circulation directly impacted the detection of pdm09 in pigs. However, there was a relative absence of pdm09 circulation in humans during the 2020-21 season that was not reflected in swine. During the 2020-21 season, most swine pdm09 detections originated from human-to-swine spillovers from the 2018-19 and 2019-20 seasons that persisted in swine. We identified contemporary swine pdm09 representatives of each persistent spillover and quantified cross-reactivity between human seasonal H1 vaccine strains and the swine strains using a panel of monovalent ferret antisera in hemagglutination inhibition (HI) assays. The swine pdm09s had variable antigenic reactivity to vaccine antisera, but each swine pdm09 clade exhibited significant reduction in cross-reactivity to one or more of the human seasonal vaccine strains. Further supporting zoonotic risk, we showed phylogenetic evidence for 17 swine-to-human transmission events of pdm09 from 2010 to 2021, 11 of which were not previously classified as variants, with each of the zoonotic cases associated with persistent circulation of pdm09 in pigs. These data demonstrate that reverse-zoonoses and evolution of pdm09 in swine results in viruses that are capable of zoonotic transmission and represent a potential pandemic threat.

Phylogenetic diversity statistics for all clades in a phylogeny.

The classic quantitative measure of phylogenetic diversity (PD) has been used to address problems in conservation biology, microbial ecology, and evolutionary biology. PD is the minimum total length of the branches in a phylogeny required to cover a specified set of taxa on the phylogeny. A general goal in the application of PD has been identifying a set of taxa of size k that maximize PD on a given phylogeny; this has been mirrored in active research to develop efficient algorithms for the problem. Other descriptive statistics, such as the minimum PD, average PD, and standard deviation of PD, can provide invaluable insight into the distribution of PD across a phylogeny (relative to a fixed value of k). However, there has been limited or no research on computing these statistics, especially when required for each clade in a phylogeny, enabling direct comparisons of PD between clades. We introduce efficient algorithms for computing PD and the associated descriptive statistics for a given phylogeny and each of its clades. In simulation studies, we demonstrate the ability of our algorithms to analyze large-scale phylogenies with applications in ecology and evolutionary biology. The software is available at https://github.com/flu-crew/PD_stats.

PARNAS: Objectively Selecting the Most Representative Taxa on a Phylogeny.

The use of next-generation sequencing technology has enabled phylogenetic studies with hundreds of thousands of taxa. Such large-scale phylogenies have become a critical component in genomic epidemiology in pathogens such as SARS-CoV-2 and influenza A virus. However, detailed phenotypic characterization of pathogens or generating a computationally tractable dataset for detailed phylogenetic analyses requires objective subsampling of taxa. To address this need, we propose parnas, an objective and flexible algorithm to sample and select taxa that best represent observed diversity by solving a generalized k-medoids problem on a phylogenetic tree. parnas solves this problem efficiently and exactly by novel optimizations and adapting algorithms from operations research. For more nuanced selections, taxa can be weighted with metadata or genetic sequence parameters, and the pool of potential representatives can be user-constrained. Motivated by influenza A virus genomic surveillance and vaccine design, parnas can be applied to identify representative taxa that optimally cover the diversity in a phylogeny within a specified distance radius. We demonstrated that parnas is more efficient and flexible than existing approaches. To demonstrate its utility, we applied parnas to 1) quantify SARS-CoV-2 genetic diversity over time, 2) select representative influenza A virus in swine genes derived from over 5 years of genomic surveillance data, and 3) identify gaps in H3N2 human influenza A virus vaccine coverage. We suggest that our method, through the objective selection of representatives in a phylogeny, provides criteria for quantifying genetic diversity that has application in the the rational design of multivalent vaccines and genomic epidemiology. PARNAS is available at https://github.com/flu-crew/parnas.

Cyclodextrin-assisted SERS determination of fluoroquinolone antibiotics in urine and blood plasma.

This paper describes the use of cyclodextrins (CDs) to improve the determination of fluoroquinolone antibiotics in human body fluids using surface-enhanced Raman spectroscopy (SERS). CDs were used to (i) prepare the CD-SERS substrate (synthesis and stabilization of silver nanoparticles), (ii) increase the sensitivity of the assay by enhancing the interaction between analyte molecules and the substrate, and (iii) improve the analysis accuracy by reducing the interaction between the substrate and endogenous components of body fluids. Two native CDs (α-CD and ß-CD) and two of their derivatives with hydroxypropyl groups were tested, and the best results were obtained with CD-SERS substrate prepared using native ß-CD. The CD-SERS assay has been developed and optimized for the determination of commonly used and structurally related fluoroquinolones (ciprofloxacin, norfloxacin, pefloxacin, and levofloxacin) in urine and blood plasma samples. Importantly, the non-significant difference in the interaction of the CD-modified SERS substrate with various fluoroquinolones has been successfully used to develop a versatile assay suitable for the analyte-class-specific analysis. Calibration plots were obtained for concentration ranges suitable for the determination of the antibiotics in urine (50-500 µg mL-1) and blood plasma (1-6 µg mL-1). The following figures of merit were obtained (for urine and blood plasma, respectively): RSD values are ≤15% and ≤23%, LOD values are 2.9-5.8 and 0.05-0.34 µg mL-1, recovery ranges are 96-105% and 91-111%. In addition, the influence of excessive concentrations of some main endogenous components of the body fluids on the analytical signal was studied. This step was used to evaluate possible limitations of the assay associated with the deviation of the composition of the body fluid matrix. Therefore, accounting for the short analysis time (≤15 min) and the use of a portable Raman spectrometer, the proposed assay can be suggested for therapeutic drug monitoring in hospitals.

RF-Net 2: fast inference of virus reassortment and hybridization networks.

MOTIVATION: A phylogenetic network is a powerful model to represent entangled evolutionary histories with both divergent (speciation) and convergent (e.g. hybridization, reassortment, recombination) evolution. The standard approach to inference of hybridization networks is to (i) reconstruct rooted gene trees and (ii) leverage gene tree discordance for network inference. Recently, we introduced a method called RF-Net for accurate inference of virus reassortment and hybridization networks from input gene trees in the presence of errors commonly found in phylogenetic trees. While RF-Net demonstrated the ability to accurately infer networks with up to four reticulations from erroneous input gene trees, its application was limited by the number of reticulations it could handle in a reasonable amount of time. This limitation is particularly restrictive in the inference of the evolutionary history of segmented RNA viruses such as influenza A virus (IAV), where reassortment is one of the major mechanisms shaping the evolution of these pathogens. RESULTS: Here, we expand the functionality of RF-Net that makes it significantly more applicable in practice. Crucially, we introduce a fast extension to RF-Net, called Fast-RF-Net, that can handle large numbers of reticulations without sacrificing accuracy. In addition, we develop automatic stopping criteria to select the appropriate number of reticulations heuristically and implement a feature for RF-Net to output error-corrected input gene trees. We then conduct a comprehensive study of the original method and its novel extensions and confirm their efficacy in practice using extensive simulation and empirical IAV evolutionary analyses. AVAILABILITY AND IMPLEMENTATION: RF-Net 2 is available at https://github.com/flu-crew/rf-net-2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Thermodynamic Study of Formamidinium Lead Iodide (CH5N2PbI3) from 5 to 357 K.

In the present study, the molar heat capacity of solid formamidinium lead iodide (CH5N2PbI3) was measured over the temperature range from 5 to 357 K using a precise automated adiabatic calorimeter. In the above temperature interval, three distinct phase transitions were found in ranges from 49 to 56 K, from 110 to 178 K, and from 264 to 277 K. The standard thermodynamic functions of the studied perovskite, namely the heat capacity C°p(T), enthalpy [H0(T) - H0(0)], entropy S0(T), and [G°(T) - H°(0)]/T, were calculated for the temperature range from 0 to 345 K based on the experimental data. Herein, the results are discussed and compared with those available in the literature as measured by nonclassical methods.

Cyclodextrin-assisted surface-enhanced Raman spectroscopy: a critical review.

Numerous approaches have been proposed to overcome the intrinsically low selectivity of surface-enhanced Raman spectroscopy (SERS), and the modification of SERS substrates with diverse recognition molecules is one of such approaches. In contrast to the use of antibodies, aptamers, and molecularly imprinted polymers, application of cyclodextrins (CDs) is still developing with less than 100 papers since 1993. Therefore, the main goal of this review is the critical analysis of all available papers on the use of CDs in SERS analysis, including physicochemical studies of CD complexation and the effect of CD presence on the Raman enhancement. The results of the review reveal that there is controversial information about CD efficiency and further experimental investigations have to be done in order to estimate the real potential of CDs in SERS-based analysis.

octoFLUshow: an Interactive Tool Describing Spatial and Temporal Trends in the Genetic Diversity of Influenza A Virus in U.S. Swine.

Influenza A virus (IAV) is passively surveilled in swine in the United States through a U.S. Department of Agriculture administered surveillance system. We present an interactive Web tool to visualize and explore trends in the genetic and geographic diversity of IAV derived from the surveillance system.

Thermodynamic Properties of the First-Generation Hybrid Dendrimer with "Carbosilane Core/Phenylene Shell" Structure.

The molar heat capacity of the first-generation hybrid dendrimer with a "carbosilane core/phenylene shell" structure was measured for the first time in the temperature range T = 6-600 K using a precise adiabatic vacuum calorimeter and DSC. In the above temperature interval, the glass transition of the studied compound was observed, and its thermodynamic characteristics were determined. The standard thermodynamic functions (the enthalpy, the entropy, and the Gibbs energy) of the hybrid dendrimer were calculated over the range from T = 0 to 600 K using the experimentally determined heat capacity. The standard entropy of formation of the investigated dendrimer was evaluated at T = 298.15 K. The obtained thermodynamic properties of the studied hybrid dendrimer were compared and discussed with the literature data for some of the first-generation organosilicon and pyridylphenylene dendrimers.

Taming the Duplication-Loss-Coalescence Model with Integer Linear Programming.

The duplication-loss-coalescence (DLC) parsimony model is invaluable for analyzing the complex scenarios of concurrent duplication loss and deep coalescence events in the evolution of gene families. However, inferring such scenarios for already moderately sized families is prohibitive owing to the computational complexity involved. To overcome this stringent limitation, we make the first step by describing a flexible integer linear programming (ILP) formulation for inferring DLC evolutionary scenarios. Then, to make the DLC model more scalable, we introduce four sensibly constrained versions of the model and describe modified versions of our ILP formulation reflecting these constraints. Our simulation studies showcase that our constrained ILP formulations compute evolutionary scenarios that are substantially larger than scenarios computable under our original ILP formulation and the original dynamic programming algorithm by Wu et al. Furthermore, scenarios computed under our constrained DLC models are remarkably accurate compared with corresponding scenarios under the original DLC model, which we also confirm in an empirical study with thousands of gene families.

Quartet-based inference is statistically consistent under the unified duplication-loss-coalescence model.

MOTIVATION: The classic multispecies coalescent (MSC) model provides the means for theoretical justification of incomplete lineage sorting-aware species tree inference methods. This has motivated an extensive body of work on phylogenetic methods that are statistically consistent under MSC. One such particularly popular method is ASTRAL, a quartet-based species tree inference method. Novel studies suggest that ASTRAL also performs well when given multi-locus gene trees in simulation studies. Further, Legried et al. recently demonstrated that ASTRAL is statistically consistent under the gene duplication and loss model (GDL). GDL is prevalent in evolutionary histories and is the first core process in the powerful duplication-loss-coalescence evolutionary model (DLCoal) by Rasmussen and Kellis. RESULTS: In this work, we prove that ASTRAL is statistically consistent under the general DLCoal model. Therefore, our result supports the empirical evidence from the simulation-based studies. More broadly, we prove that the quartet-based inference approach is statistically consistent under DLCoal. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Finding orthologous gene blocks in bacteria: the computational hardness of the problem and novel methods to address it.

MOTIVATION: The evolution of complexity is one of the most fascinating and challenging problems in modern biology, and tracing the evolution of complex traits is an open problem. In bacteria, operons and gene blocks provide a model of tractable evolutionary complexity at the genomic level. Gene blocks are structures of co-located genes with related functions, and operons are gene blocks whose genes are co-transcribed on a single mRNA molecule. The genes in operons and gene blocks typically work together in the same system or molecular complex. Previously, we proposed a method that explains the evolution of orthologous gene blocks (orthoblocks) as a combination of a small set of events that take place in vertical evolution from common ancestors. A heuristic method was proposed to solve this problem. However, no study was done to identify the complexity of the problem. RESULTS: Here, we establish that finding the homologous gene block problem is NP-hard and APX-hard. We have developed a greedy algorithm that runs in polynomial time and guarantees an O(ln⁡n) approximation. In addition, we formalize our problem as an integer linear program problem and solve it using the PuLP package and the standard CPLEX algorithm. Our exploration of several candidate operons reveals that our new method provides more optimal results than the results from the heuristic approach, and is significantly faster. AVAILABILITY AND IMPLEMENTATION: The software and data accompanying this paper are available under the GPLv3 and CC0 license respectively on: https://github.com/nguyenngochuy91/Relevant-Operon.

Copper nanoparticles for SERS-based determination of some cephalosporin antibiotics in spiked human urine.

Copper nanoparticles (CuNPs) were prepared through a wet chemistry method to be used as substituents for noble-metal-based materials in the determination of cephalosporin antibiotics in urine using surface-enhanced Raman spectroscopy (SERS). The synthesis of the CuNPs was optimized to maximize the analytical signal, and microwave heating was used to increase the reaction rate and improve the homogeneity of the CuNPs. Ceftriaxone (CTR), cefazolin (CZL), and cefoperazone (CPR) were used as the analytes of interest. The determination tests were performed on artificially spiked samples of real human urine with concentrations corresponding to therapeutic drug monitoring (TDM) (50-500 µg mL-1). Urine samples collected in the morning and during the day were used to account for deviations in the urine composition, and the universality of the proposed protocol was ensured by performing sample dilution as a pretreatment. The use of calibration plots in the form of Freundlich adsorption isotherms yielded linear calibration plots. All limits of detection were lower than the minimal concentrations required for TDM, equaling 7.5 (CTR), 8.8 (CZL), and 36 (CPR) µg mL-1. Comparison of CuNPs with Ag and Au nanoparticles (AgNPs and AuNPs, respectively) confirmed that CuNPs offered a competitively high Raman enhancement efficiency (for excitation at 638 nm). Further, although the CuNPs demonstrated poorer temporal stability as compared with the AgNPs and AuNPs, the use of freshly prepared CuNPs resulted in satisfactory accuracy (recovery = 93-107%). Given the short analysis time (<20 min, including the time for the synthesis of the CuNPs and the SERS measurements using a portable Raman spectrometer), low sensitivity to the presence of the primary intrinsic urine components and satisfactory figures of merit of the proposed protocol for the determination of cephalosporin antibiotics in urine, it should be suitable for use in TDM.

Exact median-tree inference for unrooted reconciliation costs.

BACKGROUND: Solving median tree problems under tree reconciliation costs is a classic and well-studied approach for inferring species trees from collections of discordant gene trees. These problems are NP-hard, and therefore are, in practice, typically addressed by local search heuristics. So far, however, such heuristics lack any provable correctness or precision. Further, even for small phylogenetic studies, it has been demonstrated that local search heuristics may only provide sub-optimal solutions. Obviating such heuristic uncertainties are exact dynamic programming solutions that allow solving tree reconciliation problems for smaller phylogenetic studies. Despite these promises, such exact solutions are only suitable for credibly rooted input gene trees, which constitute only a tiny fraction of the readily available gene trees. Standard gene tree inference approaches provide only unrooted gene trees and accurately rooting such trees is often difficult, if not impossible. RESULTS: Here, we describe complex dynamic programming solutions that represent the first nonnaïve exact solutions for solving the tree reconciliation problems for unrooted input gene trees. Further, we show that the asymptotic runtime of the proposed solutions does not increase when compared to the most time-efficient dynamic programming solutions for rooted input trees. CONCLUSIONS: In an experimental evaluation, we demonstrate that the described solutions for unrooted gene trees are, like the solutions for rooted input gene trees, suitable for smaller phylogenetic studies. Finally, for the first time, we study the accuracy of classic local search heuristics for unrooted tree reconciliation problems.

Determination of methotrexate in spiked human urine using SERS-active sorbent.

This report is dedicated to determination of anticancer drug methotrexate (MTX) in human urine using surface-enhanced Raman spectroscopy (SERS). Aluminum oxide loaded with silver nanoparticles (AO-Ag) was proposed as SERS-active sorbent and used for solid-phase extraction (SPE) of the analyte and its SERS-based determination (SPE-SERS protocol). MTX has strong SERS signal only in alkaline media that challenges its determination in urine due to strong background signal caused by creatinine. The application of SPE step enables to purify and concentrate the analyte making MTX determination possible. Also, the application of the same material for SPE pretreatment and SERS analysis enables to simplify and speed-up the protocol. The protocol was developed and tested using artificially spiked samples of human urine collected during different time of day to account deviating composition of the urine matrix. The use of dilution step of the analyte-containing urine was proposed prior SPE-SERS protocol to reduce the difference between morning-time- and daytime-collected urine achieving maximal reliability of the analysis. Additional physicochemical study was performed to estimate an influence of the primary intrinsic urine components (salts, urea, creatinine) and their mixtures on the analytical signal. Final protocol enables MTX determination in human urine within 20-300 µg mL-1 range of concentrations with satisfactory precision (11-19% RSD), accuracy (97-104% apparent recovery), and limit of detection (4.2 µg mL-1). Accounting that the analysis requires less than 15 min and portable Raman spectrometer, the protocol seems to be promising for therapeutic drug monitoring in hospitals to identify poor MTX clearance in a timely manner and minimize adverse effects of therapy. Graphical Abstract.

Optical sensors for determination of biogenic amines in food.

This review presents the state-of-the-art of optical sensors for determination of biogenic amines (BAs) in food by publications covering about the last 10 years. Interest in the development of rapid and preferably on-site methods for quantification of BAs is based on their important role in implementation and regulation of various physiological processes. At the same time, BAs can develop in different kinds of food by fermentation processes or microbial activity or arise due to contamination, which induces toxicological risks and food poisoning and causes serious health issues. Therefore, various optical chemosensor systems have been devised that are easy to assemble and fast responding and low-cost analytical tools. If amenable to on-site analysis, they are an attractive alternative to existing instrumental analytical methods used for BA determination in food. Hence, also portable sensor systems or dipstick sensors are described based on various probes that typically enable signal readouts such as photometry, reflectometry, luminescence, surface-enhanced Raman spectroscopy, or ellipsometry. The quantification of BAs in real food samples and the design of the sensors are highlighted and the analytical figures of merit are compared. Future instrumental trends for BA sensing point to the use of cell phone-based fully automated optical evaluation and devices that could even comprise microfluidic micro total analysis systems.

Liquid-liquid extraction-assisted SERS-based determination of sulfamethoxazole in spiked human urine.

The determination of antibiotic levels in body fluids is of great importance in the field of personalized medicine and therapeutic drug monitoring. We report on the determination of sulfamethoxazole (SMX), an antibacterial drug of the sulfanilamide class, in spiked human urine. The protocol is based on the combination of surface-enhanced Raman spectroscopy (SERS) and liquid-liquid extraction (LLE-SERS analysis). First, the urine was diluted to reduce its buffer properties and the influence of the intrinsic urine components on the background SERS signal. Second, the acidification of the diluted urine and SMX extracts was performed to facilitate SMX extraction by chloroform and suppress the background signal, respectively. Finally, the SMX determination process was performed using hydroxylamine-stabilized silver nanoparticles as the SERS substrate. The efficiency and reliability of the LLE-SERS analysis were studied using spiked urine samples obtained from healthy volunteers with an SMX content within the therapeutically relevant concentration range (10-200 µg mL-1). Additionally, the verification of the analysis protocol was done using spiked urine samples obtained from oncology patients. The results of the verification demonstrate the applicability of the analysis for quantitative therapeutic drug monitoring due to the (i) strong suppression of the background SERS signal, which occurs as the result of LLE, dilution, and pH adjusting, (ii) satisfactory limit of detection of 1.7 µg mL-1, and (iii) simple, relatively fast (∼30 min), and cost-effective sample pretreatment.

Application of Aluminum Hydroxide for Improvement of Label-Free SERS Detection of Some Cephalosporin Antibiotics in Urine.

This report is dedicated to development of surface-enhanced Raman spectroscopy (SERS) based analysis protocol for detection of antibiotics in urine. The key step of the protocol is the pretreatment of urine before the detection to minimize background signal. The pretreatment includes extraction of intrinsic urine components using aluminum hydroxide gel (AHG) and further pH adjusting of the purified sample. The protocol was tested by detection of a single antibiotic in artificially spiked samples of real urine. Five antibiotics of cephalosporin class (cefazolin, cefoperazone, cefotaxime, ceftriaxone, and cefuroxime) were used for testing. SERS measurements were performed using a portable Raman spectrometer with 638 nm excitation wavelength and silver nanoparticles as SERS substrate. The calibration curves of four antibiotics (cefuroxime is the exception) cover the concentrations required for detection in patient's urine during therapy (25/100‒500 µg/mL). Random error of the analysis (RSD < 20%) and limits of quantification (20‒90 µg/mL) for these antibiotics demonstrate the applicability of the protocol for reliable quantitative detection during therapeutic drug monitoring. The detection of cefuroxime using the protocol is not sensitive enough, allowing only for qualitative detection. Additionally, time stability and batch-to-batch reproducibility of AHG were studied and negative influence of the pretreatment protocol and its limitations were estimated and discussed.

Computing Manhattan Path-Difference Median Trees: A Practical Local Search Approach.

Median tree problems are powerful tools for inferring large-scale phylogenetic trees that hold enormous promise for society at large. Such problems seek a median tree for a given collection of input trees under some problem-specific distance. Here, we introduce a median tree problem under the classic Manhattan path-difference distance. We show that this problem is NP-hard, devise an ILP formulation, and provide an effective local search heuristic that is based on solving a local search problem exactly. Our algorithm for the local search problem improves asymptotically by a factor of $n$n on the best-known (naïve) solution, where $n$n is the overall number of taxa in the input trees. Finally, comparative phylogenetic studies using considerably large empirical data and an accuracy analysis for smaller phylogenetic trees reveal the ability of our novel heuristic.