Global versus Country-Specific Shocks and International Business Cycles

This paper documents the relative importance of global and country-specific shocks for international business cycles. For this purpose, we rely on a symmetric two-country, dynamic, general-equilibrium model with costly, incomplete, international financial markets. We also relate exogenous technologies and government expenditures to unobservable common and idiosynchratic components, and apply a Kalman filter to extract the associated global and country-specific shocks. We show that the baseline parametrization of the model, including all shocks, closely matches the cyclical fluctuations of key macroeconomic variables for the United States and a non-US aggregate over the post-1975 period. We then experiment alternative parametrizations, isolating the effects of each shock, and find that country-specific technology shocks constitute a prime determinant of international business cycles. Also, global technology shocks have marginal contributions, whereas global and country-specific government-expenditure shocks have negligible effects on cyclical fluctuations.General Equilibrium, Kalman Filter, Symmetric Economies.

Global versus Country-Specific Shocks and International Business Cycles

This paper documents the relative importance of global and country-specific shocks for international business cycles. For this purpose, we rely on a symmetric two-country, dynamic, general-equilibrium model with costly, incomplete, international financial markets. We also relate exogenous technologies and government expenditures to unobservable common and idiosynchratic components, and apply a Kalman filter to extract the associated global and country-specific shocks. We show that the baseline parametrization of the model, including all shocks, closely matches the cyclical fluctuations of key macroeconomic variables for the United States and a non-US aggregate over the post-1975 period. We then experiment alternative parametrizations, isolating the effects of each shock, and find that country-specific technology shocks constitute a prime determinant of international business cycles. Also, global technology shocks have marginal contributions, whereas global and country-specific government-expenditure shocks have negligible effects on cyclical fluctuations.General Equilibrium, Kalman Filter, Symmetric Economies

Expanding Trade within Africa: The Impact of Trade Facilitation

This paper examines the impact of trade facilitation on intra-African trade. The authors examine the role of trade facilitation reforms, such as increased port efficiency, improved customs, and regulatory environments, and upgrading services infrastructure on trade between African countries. They also consider how regional trade agreements relate to intra-African trade flows. Using trade data from 2003 to 2004, they find that improvement in ports and services infrastructure promise relatively more expansion in intra-African trade than other measures. They also show that, almost all regional trade agreements have a positive effect on trade flowsTrade; Africa; Regional Integration; Trade Facilitation

Unbiased taxonomic annotation of metagenomic samples

The classification of reads from a metagenomic sample using a reference taxonomy is usually based on first mapping the reads to the reference sequences and then, classifying each read at a node under the lowest common ancestor of the candidate sequences in the reference taxonomy with the least classification error. However, this taxonomic annotation can be biased by an imbalanced taxonomy and also by the presence of multiple nodes in the taxonomy with the least classification error for a given read. In this paper, we show that the Rand index is a better indicator of classification error than the often used area under the ROC curve and F-measure for both balanced and imbalanced reference taxonomies, and we also address the second source of bias by reducing the taxonomic annotation problem for a whole metagenomic sample to a set cover problem, for which a logarithmic approximation can be obtained in linear time.Peer ReviewedPostprint (author's final draft

Unbiased taxonomic annotation of metagenomic samples

The classification of reads from a metagenomic sample using a reference taxonomy is usually based on first mapping the reads to the reference sequences and then classifying each read at a node under the lowest common ancestor of the candidate sequences in the reference taxonomy with the least classification error. However, this taxonomic annotation can be biased by an imbalanced taxonomy and also by the presence of multiple nodes in the taxonomy with the least classification error for a given read. In this article, we show that the Rand index is a better indicator of classification error than the often used area under thereceiver operating characteristic (ROC) curve andF-measure for both balanced and imbalanced reference taxonomies, and we also address the second source of bias by reducing the taxonomic annotation problem for a whole metagenomic sample to a set cover problem, for which a logarithmic approximation can be obtained in linear time and an exact solution can be obtained by integer linear programming. Experimental results with a proof-of-concept implementation of the set cover approach to taxonomic annotation in a next release of the TANGO software show that the set cover approach further reduces ambiguity in the taxonomic annotation obtained with TANGO without distorting the relative abundance profile of the metagenomic sample.Peer ReviewedPostprint (published version

Management at the service of research: ReOmicS, a quality management system for omics sciences

AbstractManagement and research represent a binomial almost unknown, whose potentialities and requirements have not yet been fully exploited even if, recently, the scientific and social communities have felt the burden of producing results and data requiring at the same time reproducibility, reliability, safety and efficacy of the discoveries, as well as a profitable use of resources. A Quality Management System (QMS) could represent a valid tool for these purposes, improving the quality of the research. The research community could ask whether and how it is possible to apply this approach in a research laboratory without hindering their creativity, and what the possible benefits might be. On the other hand, an international standard for a quality management system appropriate for a research laboratory is yet to come. The choice, the design and the application of a QMS, inspired by the Good Laboratory Practices, in a research laboratory specialized on "omics" sciences, is fully described in this paper. Its application has already shown good outcomes as testified by specific metric of efficiency and effectiveness. The approach is innovative as there is no obvious requirement for research laboratories to develop and define quality objectives. The paper highlights how the QMS approach enhances the relationship with public and private sectors by increasing customer confidence and loyalty, as well as improving the overall performance of the laboratory in terms of throughput and value of research. These results encourage proposing it as a QMS model providing a new and scalable operational strategy to be applied in a research environment with the same target and even in a generic research laboratory

The Microbial Community Associated with Rhizostoma pulmo: Ecological Significance and Potential Consequences for Marine Organisms and Human Health

Jellyfish blooms are frequent and widespread in coastal areas worldwide, often associated with significant ecological and socio-economic consequences. Recent studies have also suggested cnidarian jellyfish may act as vectors of bacterial pathogens. The scyphomedusa Rhizostoma pulmo is an outbreak-forming jellyfish widely occurring across the Mediterranean basin. Using combination of culture-based approaches and a high-throughput amplicon sequencing (HTS), and based on available knowledge on a warm-affinity jellyfish-associated microbiome, we compared the microbial community associated with R. pulmo adult jellyfish in the Gulf of Taranto (Ionian Sea) between summer (July 2016) and winter (February 2017) sampling periods. The jellyfish-associated microbiota was investigated in three distinct compartments, namely umbrella, oral arms, and mucus secretion. Actinobacteria, Bacteroidetes, Chlamydiae, Cyanobacteria, Deinococcus-Thermus, Firmicutes, Fusobacteria, Planctomycetes, Proteobacteria, Rhodothermaeota, Spirochaetes, Tenericutes, and Thaumarchaeota were the phyla isolated from all the three R. pulmo compartments in the sampling times. In particular, the main genera Mycoplasma and Spiroplasma, belonging to the class Mollicutes (phylum Tenericutes), have been identified in all the three jellyfish compartments. The taxonomic microbial data were coupled with metabolic profiles resulting from the utilization of 31 different carbon sources by the BIOLOG Eco-Plate system. Microorganisms associated with mucus are characterized by great diversity. The counts of culturable heterotrophic bacteria and potential metabolic activities are also remarkable. Results are discussed in terms of R. pulmo ecology, the potential health hazard for marine and human life as well as the potential biotechnological applications related to the associated microbiome

ITSoneDB: a reliable resource for the investigation of the human mycobiome

Aim: In the last ten years the human microbiome investigation has raised a constantly increasing interest both in the scientific community and in public opinion. The gained evidences have clearly defined how it deeply influences both the physiological and pathological processes. Even if most of the attention was focused on prokaryotes, more recently the survey of fungal communities, the so called mycobiome [1], gained momentum. In this framework, the advent of Next Generation Sequencing (NGS) technologies and the DNA metabarcoding (exploits marker genes to taxonomically classify species) has allowed to rapidly and accurately investigate complex microbiomes. Regarding the mycobiome, the ITS1 (Internal Transcribed Spacer 1) of the eukaryotic ribosomal gene cluster is the most promising marker. The taxonomic annotation of microbial species relies on well-curated databases. In this respect we carried out a benchmark assessment of ITSoneDB [2] and UNITE [3] as reference databases for the investigation of fungal communities. Method: In order to obtain an in-silico fungal mock community we have randomly drawn 1,000 fungal genomes from the Genome NCBI database. The ITS1 regions were in-silico amplified by using primersearch and an in-house developed Python script. Then, Illumina 2x250 paired end ITS1 sequence amplicons have been generated in silico by using the Art-Illumina software. The obtained mock community includes 109 Families, 163 Genera and 73 Species. The sequences have been analysed by using QIIME2 by using both ITSoneDB and UNITE as reference databases. Results: The databases performances in correctly profiling the mycobiome relative abundances have been assessed at Family, Genus and Species ranks by using the Pearson correlation (R2). Both ITSoneDB and UNITE have shown a R2=1 at Family and Genera level. At the Species level ITSoneDB outperformed UNITE by obtaining more accurate results both in terms of classified sequences (Table 1) and relative abundance correlation (Figure 1). Conclusion: UNITE taxonomic assignments were very consistent at Family and Genus levels but not at species rank. Remarkably, as ITSoneDB results are consistent at every taxonomic level it represents a state of the art resource for the metabarcoding-based investigation of fungal microbial communities

Analysis of microbiome in gastrointestinal stromal tumors: Looking for different players in tumorigenesis and novel therapeutic options

Carcinogenesis; Microbiome; Tumor evolutionCarcinogènesi; Microbioma; Evolució del tumorCarcinogénesis; Microbioma; Evolución del tumorPreclinical forms of gastrointestinal stromal tumor (GIST), small asymptomatic lesions, called microGIST, are detected in approximately 30% of the general population. Gastrointestinal stromal tumor driver mutation can be already detected in microGISTs, even if they do not progress into malignant cancer; these mutations are necessary, but insufficient events to foster tumor progression. Here we profiled the tissue microbiota of 60 gastrointestinal specimens in three different patient cohorts—micro, low-risk, and high-risk or metastatic GIST—exploring the compositional structure, predicted function, and microbial networks, with the aim of providing a complete overview of microbial ecology in GIST and its preclinical form. Comparing microGISTs and GISTs, both weighted and unweighted UniFrac and Bray–Curtis dissimilarities showed significant community-level separation between them and a pronounced difference in Proteobacteria, Firmicutes, and Bacteroidota was observed. Through the LEfSe tool, potential microbial biomarkers associated with a specific type of lesion were identified. In particular, GIST samples were significantly enriched in the phylum Proteobacteria compared to microGISTs. Several pathways involved in sugar metabolism were also highlighted in GISTs; this was expected as cancer usually displays high aerobic glycolysis in place of oxidative phosphorylation and rise of glucose flux to promote anabolic request. Our results highlight that specific differences do exist in the tissue microbiome community between GIST and benign lesions and that microbiome restructuration can drive the carcinogenesis process.Francesca Goriini and Federica Zanotti have been supported by Fondazione Cassa di Risparmio di Bologna

A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development