pyFoldX: enabling biomolecular analysis and engineering along structural ensembles

Recent years have seen an increase in the number of structures available, not only for new proteins but also for the same protein crystallized with different molecules and proteins. While protein design software have proven to be successful in designing and modifying proteins, they can also be overly sensitive to small conformational differences between structures of the same protein. To cope with this, we introduce here pyFoldX, a python library that allows the integrative analysis of structures of the same protein using FoldX, an established forcefield and modeling software. The library offers new functionalities for handling different structures of the same protein, an improved molecular parametrization module, and an easy integration with the data analysis ecosystem of the python programming language.Availability and implementationpyFoldX is an open-source library that uses the FoldX software for energy calculations and modelling. The latter can be downloaded upon registration in http://foldxsuite.crg.eu/ and is free of charge for academics. Full details on installation, tutorials covering the library functionality, and the scripts used to generate the data and figures presented in this paper are available at https://github.com/leandroradusky/pyFoldX.

Ticks infesting humans and associated pathogens: a cross-sectional study in a 3-year period (2017–2019) in northwest Italy

Background Tick-borne diseases are common throughout Europe. Ticks transmit pathogens to the host while feeding and together with mosquitoes, they are major vectors of infectious agents worldwide. In recent years, there has been a marked increase in the incidence of tick-bite events and tick-borne disease in northwest Italy, but information on the prevalence of tick-borne pathogens in ticks removed from humans remains scarce. To fill this gap, we report here the prevalence of tick bites and tick-borne pathogens documented for humans in Piedmont, northwest Italy, in the 3-year period 2017–2019. Methods Ticks attached to humans during 2017–2019 were collected from residents of urban and rural area by physicians and veterinarians working with local veterinary agencies. All ticks (n = 1290) were morphologically identified to the species level. A subset of ticks removed from children (age 0–18 years) and the elderly (> 70 years), both age groups considered to be at-risk populations, was screened by biomolecular analysis to detect pathogens (e.g. Rickettsia spp., Borrelia spp., Anaplasma spp.). Pathogen identity was confirmed by Sanger sequencing. Results Ticks were taxonomically assigned to ten species of six genera (Amblyomma, Dermacentor, Haemaphysalis, Hyalomma, Ixodes and Rhipicephalus). Most belonged to the genus Ixodes: 1009 ticks (78.22%) were classified as Ixodes ricinus. A subset of 500 ticks collected from the two at-risk populations were subjected to PCR assay to determine the presence of Rickettsia spp., Borrelia spp., and Anaplasma spp. The overall prevalence of infection was 22.8% (n = 114; 95% confidence interval [CI]: 19.19–26.73%), meaning that at least one pathogen was detected: Rickettsia spp. (prevalence 15%, n = 76; 95% CI 12.17–18.65%); Borrelia spp. (prevalence 6.4%, n = 32; 95% CI 4.42–8.92%); and Anaplasma spp. (prevalence 1.2%, n = 6; 95% CI 0.44–2.6%). Conclusions Our data underline the importance of surveillance in the epidemiology of tick-borne diseases and the implementation of strategies to control tick infestation and associated pathogens.

A new approach for microbiological characterization of activated sludge: from the sample to the biomolecular analysis

The growing biomass in the wastewater treatment plant is called "activated sludge"; usually it is mainly composed by bacteria (95%) and by Protozoa and Metazoans (5%). The sludge biological composition is a good indicator of the wastewater treatment plant state of health. In this study, an initial characterization of the microorganisms present in the activated sludge is carried out through DNA analysis.The aim of this activity is the development of the procedures for the characterization of the sludge of the biological oxidation lines, to identify microorganism throught a new approach using biomolecular analysis and the definition of new standard protocols.

Girding the loins? Direct evidence of the use of a medieval English parchment birthing girdle from biomolecular analysis

In this paper, we describe palaeoproteomic evidence obtained from a stained medieval birth girdle using a previously developed dry non-invasive sampling technique. The parchment birth girdle studied (Wellcome Collection Western MS. 632) was made in England in the late fifteenth century and was thought to be used by pregnant women while giving birth. We were able to extract both human and non-human peptides from the manuscript, including evidence for the use of honey, cereals, ovicaprine milk and legumes. In addition, a large number of human peptides were detected on the birth roll, many of which are found in cervico-vaginal fluid. This suggests that the birth roll was actively used during childbirth. This study is, to our knowledge, the first to extract and analyse non-collagenous peptides from a birth girdle using this sampling method and demonstrates the potential of this type of analysis for stained manuscripts, providing direct biomolecular evidence for active use.

A lazy feature selection method for multi-label classification

In many important application domains, such as text categorization, biomolecular analysis, scene or video classification and medical diagnosis, instances are naturally associated with more than one class label, giving rise to multi-label classification problems. This has led, in recent years, to a substantial amount of research in multi-label classification. More specifically, feature selection methods have been developed to allow the identification of relevant and informative features for multi-label classification. This work presents a new feature selection method based on the lazy feature selection paradigm and specific for the multi-label context. Experimental results show that the proposed technique is competitive when compared to multi-label feature selection techniques currently used in the literature, and is clearly more scalable, in a scenario where there is an increasing amount of data.