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Article ; Online: Screening for candidate biomarkers of TB in stimulated blood: another step in the quest for a test?

Kaforou, Myrsini

2020 Volume 75, Issue 7, Page(s) 534–535

MeSH term(s)	Biomarkers/blood ; Diagnosis, Differential ; Humans ; Latent Tuberculosis/blood ; Latent Tuberculosis/diagnosis ; Tuberculin Test/methods
Chemical Substances	Biomarkers
Language	English
Publishing date	2020-06-10
Publishing country	England
Document type	Editorial ; Research Support, Non-U.S. Gov't
ZDB-ID	204353-1
ISSN	1468-3296 ; 0040-6376
ISSN (online)	1468-3296
ISSN	0040-6376
DOI	10.1136/thoraxjnl-2020-214775
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Article ; Online: Sensitivity of shotgun metagenomics to host DNA: abundance estimates depend on bioinformatic tools and contamination is the main issue.

McArdle, Andrew J / Kaforou, Myrsini

Access microbiology

2020 Volume 2, Issue 4, Page(s) acmi000104

Abstract: A recent study reported that increasing host DNA abundance and reducing read depth impairs the sensitivity of detection of low-abundance micro-organisms by shotgun metagenomics. The authors used DNA from a synthetic bacterial community with abundances ... ...

Abstract	A recent study reported that increasing host DNA abundance and reducing read depth impairs the sensitivity of detection of low-abundance micro-organisms by shotgun metagenomics. The authors used DNA from a synthetic bacterial community with abundances varying across several orders of magnitude and added varying proportions of host DNA. However, the use of a marker-gene-based abundance estimation tool (MetaPhlAn2) requires considerable depth to detect marker genes from low-abundance organisms. Here, we reanalyse the deposited data, and place the study in the broader context of low microbial biomass metagenomics. We opted for a fast and sensitive read binning tool (Kraken 2) with abundance estimates from Bracken. With this approach all organisms are detected even when the sample comprises 99 % host DNA and similarly accurate abundance estimates are provided (mean squared error 0.45 vs. 0.3 in the original study). We show that off-target genera, whether contaminants or misidentified reads, come to represent over 10 % of reads when the sample is 99 % host DNA and exceed counts of many target genera. Therefore, we applied Decontam, a contaminant detection tool, which was able to remove 61 % of off-target species and 79 % of off-target reads. We conclude that read binning tools can remain sensitive to low-abundance organisms even with high host DNA content, but even low levels of contamination pose a significant problem due to low microbial biomass. Analytical mitigations are available, such as Decontam, although steps to reduce contamination are critical.
Language	English
Publishing date	2020-02-17
Publishing country	England
Document type	Journal Article
ISSN	2516-8290
ISSN (online)	2516-8290
DOI	10.1099/acmi.0.000104
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Article ; Online: Comparative transcriptomic analysis of whole blood mycobacterial growth assays and tuberculosis patients' blood RNA profiles.

Bachanová, Petra / Cheyne, Ashleigh / Broderick, Claire / Newton, Sandra M / Levin, Michael / Kaforou, Myrsini

Scientific reports

2022 Volume 12, Issue 1, Page(s) 17684

Abstract: In vitro whole blood infection models are used for elucidating the immune response to Mycobacterium tuberculosis (Mtb). They exhibit commonalities but also differences, to the in vivo blood transcriptional response during natural human Mtb disease. Here, ...

Abstract	In vitro whole blood infection models are used for elucidating the immune response to Mycobacterium tuberculosis (Mtb). They exhibit commonalities but also differences, to the in vivo blood transcriptional response during natural human Mtb disease. Here, we present a description of concordant and discordant components of the immune response in blood, quantified through transcriptional profiling in an in vitro whole blood infection model compared to whole blood from patients with tuberculosis disease. We identified concordantly and discordantly expressed gene modules and performed in silico cell deconvolution. A high degree of concordance of gene expression between both adult and paediatric in vivo-in vitro tuberculosis infection was identified. Concordance in paediatric in vivo vs in vitro comparison is largely characterised by immune suppression, while in adults the comparison is marked by concordant immune activation, particularly that of inflammation, chemokine, and interferon signalling. Discordance between in vitro and in vivo increases over time and is driven by T-cell regulation and monocyte-related gene expression, likely due to apoptotic depletion of monocytes and increasing relative fraction of longer-lived cell types, such as T and B cells. Our approach facilitates a more informed use of the whole blood in vitro model, while also accounting for its limitations.
MeSH term(s)	Adult ; Humans ; Child ; Transcriptome ; RNA ; Tuberculosis/microbiology ; Mycobacterium tuberculosis/genetics ; Interferons/genetics
Chemical Substances	RNA (63231-63-0) ; Interferons (9008-11-1)
Language	English
Publishing date	2022-10-21
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-022-20409-y
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Article ; Online: Comparative transcriptomic analysis reveals translationally relevant processes in mouse models of malaria.

Georgiadou, Athina / Dunican, Claire / Soro-Barrio, Pablo / Lee, Hyun Jae / Kaforou, Myrsini / Cunnington, Aubrey J

eLife

2022 Volume 11

Abstract: Recent initiatives to improve translation of findings from animal models to human disease have focussed on reproducibility but quantifying the relevance of animal models remains a challenge. Here, we use comparative transcriptomics of blood to evaluate ... ...

Abstract	Recent initiatives to improve translation of findings from animal models to human disease have focussed on reproducibility but quantifying the relevance of animal models remains a challenge. Here, we use comparative transcriptomics of blood to evaluate the systemic host response and its concordance between humans with different clinical manifestations of malaria and five commonly used mouse models.
MeSH term(s)	Anemia ; Animals ; Disease Models, Animal ; Female ; Gene Expression Profiling/methods ; Gene Expression Profiling/standards ; Host-Parasite Interactions/genetics ; Humans ; Malaria/classification ; Malaria/parasitology ; Malaria, Falciparum/parasitology ; Mice ; Mice, Inbred C57BL ; Plasmodium/classification ; Plasmodium/genetics ; Reproducibility of Results ; Transcriptome
Language	English
Publishing date	2022-01-10
Publishing country	England
Document type	Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.70763
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Article ; Online: Transcriptomics for child and adolescent tuberculosis.

Kaforou, Myrsini / Broderick, Claire / Vito, Ortensia / Levin, Michael / Scriba, Thomas J / Seddon, James A

Immunological reviews

2022 Volume 309, Issue 1, Page(s) 97–122

Abstract: Tuberculosis (TB) in humans is caused by Mycobacterium tuberculosis (Mtb). It is estimated that 70 million children (<15 years) are currently infected with Mtb, with 1.2 million each year progressing to disease. Of these, a quarter die. The risk of ... ...

Abstract	Tuberculosis (TB) in humans is caused by Mycobacterium tuberculosis (Mtb). It is estimated that 70 million children (<15 years) are currently infected with Mtb, with 1.2 million each year progressing to disease. Of these, a quarter die. The risk of progression from Mtb infection to disease and from disease to death is dependent on multiple pathogen and host factors. Age is a central component in all these transitions. The natural history of TB in children and adolescents is different to adults, leading to unique challenges in the development of diagnostics, therapeutics, and vaccines. The quantification of RNA transcripts in specific cells or in the peripheral blood, using high-throughput methods, such as microarray analysis or RNA-Sequencing, can shed light into the host immune response to Mtb during infection and disease, as well as understanding treatment response, disease severity, and vaccination, in a global hypothesis-free manner. Additionally, gene expression profiling can be used for biomarker discovery, to diagnose disease, predict future disease progression and to monitor response to treatment. Here, we review the role of transcriptomics in children and adolescents, focused mainly on work done in blood, to understand disease biology, and to discriminate disease states to assist clinical decision-making. In recent years, studies with a specific pediatric and adolescent focus have identified blood gene expression markers with diagnostic or prognostic potential that meet or exceed the current sensitivity and specificity targets for diagnostic tools. Diagnostic and prognostic gene expression signatures identified through high-throughput methods are currently being translated into diagnostic tests.
MeSH term(s)	Adolescent ; Adult ; Child ; Gene Expression Profiling/methods ; Humans ; Mycobacterium tuberculosis ; RNA ; Transcriptome ; Tuberculosis/diagnosis ; Tuberculosis/genetics ; Tuberculosis/therapy
Chemical Substances	RNA (63231-63-0)
Language	English
Publishing date	2022-07-12
Publishing country	England
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't
ZDB-ID	391796-4
ISSN	1600-065X ; 0105-2896
ISSN (online)	1600-065X
ISSN	0105-2896
DOI	10.1111/imr.13116
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Article ; Online: Next-generation molecular diagnostics: Leveraging digital technologies to enhance multiplexing in real-time PCR

Kreitmann, Louis / Miglietta, Luca / Xu, Ke / Malpartida-Cardenas, Kenny / D'Souza, Giselle / Kaforou, Myrsini / Brengel-Pesce, Karen / Drazek, Laurent / Holmes, Alison / Rodriguez-Manzano, Jesus

Trends in Analytical Chemistry. 20232023 Mar. 04, Feb. 04, v. 160 p.116963-

2023

Abstract: Real-time polymerase chain reaction (qPCR) enables accurate detection and quantification of nucleic acids and has become a fundamental tool in biological sciences, bioengineering and medicine. By combining multiple primer sets in one reaction, it is ... ...

Abstract	Real-time polymerase chain reaction (qPCR) enables accurate detection and quantification of nucleic acids and has become a fundamental tool in biological sciences, bioengineering and medicine. By combining multiple primer sets in one reaction, it is possible to detect several DNA or RNA targets simultaneously, a process called multiplex PCR (mPCR) which is key to attaining optimal throughput, cost-effectiveness and efficiency in molecular diagnostics, particularly in infectious diseases. Multiple solutions have been devised to increase multiplexing in qPCR, including single-well techniques, using target-specific fluorescent oligonucleotide probes, and spatial multiplexing, where segregation of the sample enables parallel amplification of multiple targets. However, these solutions are mostly limited to three or four targets, or highly sophisticated and expensive instrumentation. There is a need for innovations that will push forward the multiplexing field in qPCR, enabling for a next generation of diagnostic tools which could accommodate high throughput in an affordable manner. To this end, the use of machine learning (ML) algorithms (data-driven solutions) has recently emerged to leverage information contained in amplification and melting curves (AC and MC, respectively) – two of the most standard bio-signals emitted during qPCR – for accurate classification of multiple nucleic acid targets in a single reaction. Therefore, this review aims to demonstrate and illustrate that data-driven solutions can be successfully coupled with state-of-the-art and common qPCR platforms using a variety of amplification chemistries to enhance multiplexing in qPCR. Further, because both ACs and MCs can be predicted from sequence data using thermodynamic databases, it has also become possible to use computer simulation to rationalize and optimize the design of mPCR assays where target detection is supported by data-driven technologies. Thus, this review also discusses recent work converging towards the development of an end-to-end framework where knowledge-based and data-driven software solutions are integrated to streamline assay design, and increase the accuracy of target detection and quantification in the multiplex setting. We envision that concerted efforts by academic and industry scientists will help advance these technologies, to a point where they become mature and robust enough to bring about major improvements in the detection of nucleic acids across many fields.
Keywords	DNA ; RNA ; analytical chemistry ; computer simulation ; computer software ; cost effectiveness ; diagnostic techniques ; fluorescence ; industry ; instrumentation ; medicine ; oligonucleotides ; quantitative polymerase chain reaction ; thermodynamics ; Real-time polymerase chain reaction ; Machine learning ; Amplification curve analysis ; Melting curve analysis ; Nucleic acid amplification techniques ; Molecular diagnostics
Language	English
Dates of publication	2023-0204
Publishing place	Elsevier B.V.
Document type	Article ; Online
ZDB-ID	2014041-1
ISSN	0165-9936
ISSN	0165-9936
DOI	10.1016/j.trac.2023.116963
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Article ; Online: Predicting active tuberculosis progression by RNA analysis.

Levin, Michael / Kaforou, Myrsini

Lancet (London, England)

2016 Volume 387, Issue 10035, Page(s) 2268–2270

MeSH term(s)	Humans ; Tuberculosis/diagnosis
Language	English
Publishing date	2016-06-04
Publishing country	England
Document type	Comment ; Journal Article
ZDB-ID	3306-6
ISSN	1474-547X ; 0023-7507 ; 0140-6736
ISSN (online)	1474-547X
ISSN	0023-7507 ; 0140-6736
DOI	10.1016/S0140-6736(16)00165-3
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Article ; Online: Impaired in vitro Interferon-γ production in patients with visceral leishmaniasis is improved by inhibition of PD1/PDL-1 ligation.

Takele, Yegnasew / Adem, Emebet / Franssen, Susanne Ursula / Womersley, Rebecca / Kaforou, Myrsini / Levin, Michael / Müller, Ingrid / Cotton, James Anthony / Kropf, Pascale

PLoS neglected tropical diseases

2022 Volume 16, Issue 6, Page(s) e0010544

Abstract: Visceral leishmaniasis (VL) is a neglected tropical disease that causes substantial morbidity and mortality and is a growing health problem in Ethiopia, where this study took place. Most individuals infected with Leishmania donovani parasites will stay ... ...

Abstract	Visceral leishmaniasis (VL) is a neglected tropical disease that causes substantial morbidity and mortality and is a growing health problem in Ethiopia, where this study took place. Most individuals infected with Leishmania donovani parasites will stay asymptomatic, but some develop VL that, if left untreated, is almost always fatal. This stage of the disease is associated with a profound immunosuppression, characterised by impaired production of Interferonγ (IFNγ), a cytokine that plays a key role in the control of Leishmania parasites, and high expression levels of an inhibitory receptor, programmed cell death 1 (PD1) on CD4+ T cells. Here, we tested the contribution of the interaction between the immune checkpoint PD1 and its ligand PDL-1 on the impaired production of IFNγ in VL patients. Our results show that in the blood of VL patients, not only CD4+, but also CD8+ T cells express high levels of PD1 at the time of VL diagnosis. Next, we identified PDL-1 expression on different monocyte subsets and neutrophils and show that PDL-1 levels were significantly increased in VL patients. PD1/PDL-1 inhibition resulted in significantly increased production of IFNγ, suggesting that therapy using immune checkpoint inhibitors might improve disease control in these patients.
MeSH term(s)	CD4-Positive T-Lymphocytes ; CD8-Positive T-Lymphocytes ; Humans ; Interferon-gamma/metabolism ; Leishmania donovani ; Leishmaniasis, Visceral/parasitology
Chemical Substances	Interferon-gamma (82115-62-6)
Language	English
Publishing date	2022-06-24
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2429704-5
ISSN	1935-2735 ; 1935-2735
ISSN (online)	1935-2735
ISSN	1935-2735
DOI	10.1371/journal.pntd.0010544
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Article ; Online: Placental macrophage responses to viral and bacterial ligands and the influence of fetal sex.

Pantazi, Paschalia / Kaforou, Myrsini / Tang, Zhonghua / Abrahams, Vikki M / McArdle, Andrew / Guller, Seth / Holder, Beth

iScience

2022 Volume 25, Issue 12, Page(s) 105653

Abstract: Bacterial and viral infections of the placenta are associated with inflammation and adverse pregnancy outcomes. Hofbauer cells (HBCs) are fetal-origin macrophages in the placenta, proposed to protect the fetus from vertical pathogen transmission. We ... ...

Abstract	Bacterial and viral infections of the placenta are associated with inflammation and adverse pregnancy outcomes. Hofbauer cells (HBCs) are fetal-origin macrophages in the placenta, proposed to protect the fetus from vertical pathogen transmission. We performed quantitative proteomics on term HBCs under resting conditions and following exposure to bacterial and viral pathogen-associated molecular patterns (PAMPs), and investigated the contribution of fetal sex. Resting HBCs expressed proteins pertinent to macrophage function, including chemokines, cytokines, Toll-like receptors, and major histocompatibility complex class I and II molecules. HBCs mounted divergent responses to bacterial versus viral PAMPs but exhibited protein expression changes suggestive of a more pro-inflammatory phenotype. A comparison between male and female HBCs showed that the latter mounted a stronger and wider response. Here, we provide a comprehensive understanding of the sex-dependent responses of placental macrophages to infectious triggers, which were primarily associated with lipid metabolism in males and cytoskeleton organization in females.
Language	English
Publishing date	2022-11-22
Publishing country	United States
Document type	Journal Article
ISSN	2589-0042
ISSN (online)	2589-0042
DOI	10.1016/j.isci.2022.105653
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Article: Discrimination of bacterial and viral infection using host-RNA signatures integrated in a lab-on-chip platform

Pennisi, Ivana / Moniri, Ahmad / Miscourides, Nicholas / Miglietta, Luca / Moser, Nicolas / Habgood-Coote, Dominic / Herberg, Jethro A. / Levin, Michael / Kaforou, Myrsini / Rodriguez-Manzano, Jesus / Georgiou, Pantelis

Biosensors & bioelectronics. 2022 Aug. 09,

2022

Abstract: The unmet clinical need for accurate point-of-care (POC) diagnostic tests able to discriminate bacterial from viral infection demands a solution that can be used both within healthcare settings and in the field, and that can also stem the tide of ... ...

Abstract	The unmet clinical need for accurate point-of-care (POC) diagnostic tests able to discriminate bacterial from viral infection demands a solution that can be used both within healthcare settings and in the field, and that can also stem the tide of antimicrobial resistance. Our approach to solve this problem combine the use of host gene signatures with our Lab-on-a-chip (LoC) technology enabling low-cost POC expression analysis to detect Infectious Disease. Transcriptomics have been extensively investigated as a potential tool to be implemented in the diagnosis of infectious disease. On the other hand, LoC technologies using Ion-sensitive field-effect transistor (ISFET), in conjunction with isothermal chemistries, are offering a promising alternative to conventional amplification instruments, owing to their portable and affordable nature. Currently, the data analysis of ISFET arrays are restricted to established methods by averaging the output of every sensor to give a single time-series. This simple approach makes unrealistic assumptions, leading to insufficient performance for applications that require accurate quantification such as Host-Transcriptomics. In order to reliably quantify transcripts on our LoC platform enabling the classification of infectious disease on-chip, we propose a novel data-driven algorithm for extracting time-to-positive values from ISFET arrays. The algorithm proposed correctly outputs a time-to-positive for all the reactions, with a high correlation to RT-qLAMP (0.85, R² = 0.98, p < 0.01), resulting in a classification accuracy of 100% (CI, 95–100%). This work aims to bridge the gap between translating assays from microarray analysis to ISFET arrays providing benefits on tackling infectious disease and diagnostic testing in hard-to-reach areas of the world.
Keywords	algorithms ; antibiotic resistance ; biosensors ; genes ; infectious diseases ; lab-on-a-chip technology ; microarray technology ; point-of-care systems ; time series analysis ; transcriptomics ; transistors
Language	English
Dates of publication	2022-0809
Publishing place	Elsevier B.V.
Document type	Article
Note	Pre-press version
ZDB-ID	1011023-9
ISSN	1873-4235 ; 0956-5663
ISSN (online)	1873-4235
ISSN	0956-5663
DOI	10.1016/j.bios.2022.114633
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