Escherichia coli PNPase can act not only as an RNA degrading enzyme but also by an unknown mechanism as a chaperone for small regulatory RNAs (sRNAs), with pleiotropic consequences for gene regulation. We present structures of the ternary assembly formed by PNPase, the RNA chaperone Hfq, and sRNA and show that this complex boosts sRNA stability in vitro. Comparison of structures for PNPase in RNA carrier and degradation modes reveals how the RNA is rerouted away from the active site through interactions with Hfq and the KH and S1 domains. Together, these data explain how PNPase is repurposed to protect sRNAs from cellular ribonucleases such as RNase E and could aid RNA presentation to facilitate regulatory actions on target genes.Polynucleotide phosphorylase (PNPase) is an ancient exoribonuclease conserved in the course of evolution and is found in species as diverse as bacteria and humans. Paradoxically,   •Cryo-EM structures of PNPase in complex with the RNA chaperone Hfq and regulatory RNA•Structural insights into regulatory RNA recognition by Hfq and PNPase•Model for stabilization of regulatory RNAs and facilitation of their functions The conserved exoribonuclease PNPase contributes to RNA turnover in many organisms, but in bacteria the enzyme can be re-programmed by the RNA chaperone Hfq and regulatory RNA to switch from degradative to chaperoning roles in RNA-mediated gene regulation. Dendooven et al. provide structural insight into the basis for this functional switch and details of the recognition of complex regulatory RNAs by Hfq and PNPase. In all domains of life, ribonucleases are key players in post-transcriptional regulation of gene expression. These enzymes catalyze mRNA degradation and the maturation of rRNA and tRNA precursors, and they often have an impact on the stability of regulatory RNAs . One of Listeria monocytogenes and Staphylococcus epidermidis, participates in CRISPR systems  was used to solve structures for E. coli PNPase in the apo- and substrate-bound forms and in a ternary complex with sRNA substrate and Hfq . In our model of the RNA carrier complex, Hfq cooperates with the KH and S1 structural modules of PNPase to capture the RNA and prevent the 3ʹ end from entering the central channel, thereby safeguarding it from degradation. A degenerate ARN-repeat sequence in the RNA substrate interacts with one of the Hfq RNA-binding surfaces, bridging Hfq and PNPase, and indicating a loose sequence preference for carrier assembly. In vivo reporter assays indicate the KH-S1-sRNA interactions in the RNA carrier assembly are important for cellular stability of sRNAs. We also demonstrate how the PNPase-Hfq carrier complex protects sRNAs from degradation by other ribonucleases in vitro and at the same time can facilitate handover of the sRNA to its RNA target. These results show how ribonucleoprotein complexes involving RNA chaperones can support RNA-mediated control processes and contribute to their regulatory repertoire.We present results that illuminate how E. coli apo PNPase have been limited to the catalytic core and parts of the KH domains .53D variability analysis of the particle images was performed in cryoSPARC .6leuZ mediates the association of PNPase and Hfq in the RNA carrier assembly and that no direct protein-protein contacts are made. The 3ʹETSleuZ is engaged extensively with Hfq, interacting with the distal and proximal surfaces, and also the circumferential rim  tail associates with the Hfq proximal side, and a 5′ A-rich region interacts with the Hfq distal side . Indeed,mal face A. Moreovmal face A and 3B.bacteria . This mobacteria . Althougo-EM map C. Only to-EM map C. This po-EM map , these v domains C. These possible D. Local leuZ   B. Additisemblies F. These leuZ assembly allowed us to predict and test candidate residues in the PNPase domains that contact the sRNA in the RNA carrier complex. Three PNPase mutants were designed and evaluated for RNA and Hfq complex formation in vitro: (1) a double mutant of residues K657A and R658A in the S1 domain implicated in the interaction with RNA on the distal side of Hfq ; (2) a double mutant of the KH domain residues K566A and K571A involved in binding the RNA stem loop ; and (3) a quadruple mutant of S1 domain residues R681A, Q682A, R684A, and R686A on a basic loop predicted to bind 3ʹETSleuZ extensively   and CyaR (class II), which have been shown previously to form RNA carrier assemblies with PNPase (The model for the PNPase-Hfq-3ʹETSse S1x4) C. Three h PNPase .All purified PNPase mutants were able to degrade RNA substrates but exhibited lower levels of activity compared with wild-type enzyme , in agrein vivo, we first examined the impact of the PNPase mutants on CyaR and RyhB stability after inhibition of transcription initiation by rifampicin treatment. As shown in leuZ stability . This processed form of 3ʹETSleuZ has a monophosphorylated 5ʹ end, making it a suitable substrate for RNase E. We confirmed that the processed 5ʹP-3ʹETSleuZ∗ can form a PNPase-Hfq-3ʹETSleuZ∗ complex . However, the base-pairing region between these RNAs spans 19 nt  is engaged. The capacity of PNPase to form ribonucleoprotein assemblies or bind allosteric ligands reflects on the biological importance of modulating the enzyme  localizes between the mitochondrial inner and outer membranes . Many roE. coli, the S1 protein of the ribosomal small subunit has a string of four S1 RNA binding modules that promote accommodation into the decoding channel of the 30S subunit .Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Ben F. Luisi Cryo-EM maps and models generated in this study are available at EMBD (accession codes PDB ID E. coli K12 strain MG1655 (RRID:Addgene_61440) or BL21DE3. Depending on the experiment, the strains were grown at 37°C in LB medium (MG1655) or 2xYT medium (BL21) to early or late exponential phase.All strains used in this study are derivatives of E. coli strains and plasmids used in this study are listed in pnp gene in strain NRD1243 was replaced with a PCR product containing a cassette encoding the kanamycin resistance and ccdB toxin genes by lamba Red recombinase-mediated allele replacement. The PCR products used to generate NRD1611, NRD1612, and NRD1613 were amplified via PCR from CR201 genomic DNA using primers pnpD566-71KO For and Rev, pnpD657-8KO For and Rev, and pnpD681-6KO For and Rev, respectively. Successful recombinants were selected using LB plates containing arabinose (0.2%), which causes expression of the CcdB toxin, and validated by PCR using primers pnp For and Rev.Strains NRD1611, NRD1612, and NRD1613 were generated as follows. A portion of the ccdB kan cassette located within pnp with sequence in the DNA oligos pnpK566K571, pnpK657R658, and pnpRQRR681-6, which contain mutations in portions of pnp resulting in the K566A K571A, K657A R658A, and R681A Q682A R684A R686A substitutions, respectively.Strains NRD1614, NRD1615, and NRD1622 were created using lambda Red recombinase-mediated allele replacement to exchange the pnp with a PCR product containing a chloramphenicol resistance cassette that was amplified from NRD1137 genomic DNA using pnpfar For and Rev primers. Successful recombinants were validated by PCR and sequencing using primers pnpmidFor3 and pnp Rev.Strain NRD1617 was created by lambda Red recombinase-mediated gene replacement exchanging in vitro studies were prepared by two successive PCR reactions. In the first step, two fragments were PCR-amplified using the wild-type PNPase gene as a template: one using the forward primer PNPaseNcoFor and a reverse primer introducing the mutation (primers PNPaseS1x2Rev or PNPaseKHx2Rev or PNPaseS1x4Rev) (Mutants of the PNPase gene for S1x4Rev) ; the othS1x4Rev) . PCR proEscherichia coli PNPase and Hfq were prepared using the protocols described earlier (pnp E. coli strain (NRD1617) was used. earlier . For exp600 0.45. 3 h after induction, cells were harvested by centrifugation, resuspended in lysis buffer ) and flash frozen in liquid nitrogen. Upon thawing the cells were passed thrice through an EmulsiFlex-05 (Avestin) cell disruptor and the lysate was clarified with centrifugation. Subsequently, the lysate was incubated at 85°C for 20 mins and centrifuged again. Ammonium sulfate was added to the supernatant up to 1.5 M followed by another centrifugation step. The final supernatant was loaded onto a HiTrap Butyl–Sepharose column  equilibrated with HfqA buffer 2SO4). Proteins were eluted with an isocratic gradient of HfqB buffer (50 mM Tris pH 8.0) and aliquots of fractionated elutant analyzed by SDS–PAGE. Fractions enriched with Hfq were pooled, concentrated and loaded onto a Sephadex 75 gel filtration column  equilibrated with HfqC buffer ). Fractions were analyzed by SDS–PAGE and the concentration of clean Hfq fractions was determined spectroscopically using a NanoDrop ND-1000 spectrophotometer (Thermo Scientific) and a λ280nm extinction coefficient of 4470 M-1cm-1 (per Hfq protomer) before the samples were flash frozen and stored at −80°C.For Hfq preparations, pEH-10-(hfq) was transformed into BL21(DE3) cells. 2 × YT media (Formedium) supplemented with 100 μg/ml carbenicillin was inoculated with starter culture and grown at 37°C. The cultures were induced with 1 mM IPTG at ODpnp (NRD1617) (PNPase mutants). 2 × YT media (Formedium) supplemented with 100 μg/ml carbenicillin was inoculated with precultures and grown at 37°C. The cultures were induced with 0.5 mM IPTG at OD600 0.45 and the temperature was reduced to 25°C. 3-4 h after induction cells were harvested by centrifugation , resuspended in lysis buffer ) and flash frozen in liquid nitrogen.For the PNPase procedure, pET_Duet_pnpwt was transformed into BL21(DE3) (wild-type PNPase) or BL21(DE3) Δ2, 45 mM Na phosphate pH 7.9, 0.9 M (NH4)2SO4 and 1 mM TCEP and the protein solution was loaded on a 5 mL HiTrap Butyl-Sepharose column  equilibrated with BS Buffer A 2SO4, 0.5 mM TCEP) and eluted with a 0%–66% gradient of BS Buffer B (50 mM Tris-HCl pH 7.5). Fractions containing PNPase were pooled, concentrated and loaded on a Superdex 200 10/300 GL gel filtration column  equilibrated with a buffer composed of 20 mM Tris-HCl pH 8.0, 150 mM NaCl, 5 mM MgCl2, 0.5 mM TCEP, 10% (v/v) Glycerol. Concentration of purified protein was determined spectroscopically using a NanoDrop ND-1000 spectrophotometer (Thermo Scientific) and a λ280nm extinction coefficient of 30370 M-1cm-1 (per protomer) and it was flash frozen in liquid nitrogen and stored at −80°C. All peak fractions were analyzed by SDS-PAGE.Upon thawing the cells were passed thrice through an EmulsiFlex-05 cell disruptor (Avestin) at pressure near 1000 bar and clarified by centrifugation . PNPase was precipitated from the lysate with ammonium sulfate (51.3% saturation) at 4°C. The sample was centrifuged and the pellet resuspended in Q Buffer A’ ), loaded on 5 mL HiTrap Q column  equilibrated in Q buffer A  and eluted with a 0%–60% gradient of Q Buffer B (Q Buffer A with 1 M NaCl). Fractions from the Q column were evaluated by SDS-PAGE and those containing PNPase were pooled and supplemented with 1mM MgClin vitro transcription (IVT) using standard protocol. As an IVT template PCR products were used obtained in the reaction with Phire Hotstart II polymerase (Thermo Fisher) according to manufacturer’s instructions (RyhB), or hybridized DNA oligonucleotides . The sequences of used primers and DNA oligonucleotides are summarized in All RNAs used in this study were prepared by 2, 1 mM DTT, 2 mM sodium phosphate). Degradation was started by addition of wild-type or mutant PNPase at 37°C. Samples taken from the reaction were quenched at designated time points by adding and equal volume of 0.5 mg/mL proteinase K, diluted in a buffer containing 100 mM Tris-HCl pH 7.5, 150 mM NaCl, 12.5 mM EDTA and 1% w/v SDS and incubated at 50°C for 20 min. RNA contents corresponding to each time point were run on a 8% polyacrylamide, 7.5M urea gel  in 1xTBE and visualized using Sybr Gold (Invitrogen). Quantification was performed with GeneTools (Syngene).Degradation assays were performed and complexes for native gels were assembled as previously described . For the2, 1 mM DTT, 0.5 U/μL RNase OUT (Invitrogen). RNase III assays were performed according to manufacturer’s instruction .For the truncated degradosome degradation assays  the same2, 1 mM DTT) and incubated at 30°C for 20 minutes. Subsequently, samples were transferred to ice, supplemented with 5 μL of 50% glycerol in binding buffer and immediately loaded on the PAA gel supplemented with 10% glycerol and run in tris-glycine buffer pH 8.5.For binding assays, 0.4 μM RNA was mixed with indicated proteins in binding buffer , RyhB expression was induced for 15 min by the addition of bipyridyl (250 μM). Cells were then harvested by centrifugation, washed twice with a TBS solution , and then flash frozen. After suspension in 500 μL TBS buffer containing HALT protease inhibitor (2 μl) and Superase RNase inhibitor (5 μl), cells were macerated with 0.1 mm glass beads  by vortexing for 10 min with alternating 30 s intervals of vortexing and resting on ice. Cell debris was subsequently removed by centrifugation . After additional Superase inhibitor (5 μl) was added to the cleared lysate and the volume was brought up to 1 mL with TBS buffer, a portion of each sample was reserved for RNA and protein isolation (Input). The remaining sample was subsequently incubated with 75 μL of equilibrated anti-FLAG M2 resin for 2 h at 4°C. After washing the resin four times with TBS, bound proteins were eluted by incubation for 30 min with 150 μg/ml 3xFLAG peptide in TBS. The elution (IP) and input samples were then mixed with a neutral phenol solution  by vortexing for 10 s, and the aqueous phase and organic phases were separated by centrifugation. RNA was alcohol precipitated from the aqueous phase, and protein was precipitated from the phenol fraction by addition of two volumes of ice-cold acetone. RNA and protein were suspended in DEPC-treated water and Laemmli buffer, respectively. Northern blots were performed as described below in Materials and Methods. Western blotting analysis was performed by fractionating the samples reserved for protein analysis on a 4% stacking 10% resolving SDS-PAGE gel in 1 × Tris-glycine SDS buffer at 120 V. Fractionated protein was then transferred to a 0.45 μm PVDF membrane (Thermo Scientific) at 15 V for 30 min using Trans-Blot SD semidry transfer apparatus (Bio-rad) following manufacturer’s guidelines. PNPase was detected using 1:1000 dilution of a rat anti-FLAG antibody (1:1000) and anti-rat goat IgG secondary antibody (1:2500). Hfq was detected using 1:5000 dilution of preabsorbed anti-Hfq antiserum obtained from Susan Gottesman (NCI) and goat antirabbit IgG secondary antibody.PNPase was immunoprecipitated as previously described . After c39).Overnight cultures were diluted 1:200 in fresh LB medium, grown to early exponential phase, and RyhB or CyaR were induced for 15 min by the addition of bipyridyl (250 μM) or cAMP (5 mM), respectively. 700 μL samples were taken from each culture (T = 0), rifampicin (250 μg/ml) was added to each culture, and additional samples were taken 1, 2, 5, and 10 min afterward. RNA was isolated by the hot phenol method as previously described  urea gels by electrophoresis at 55V. RNA was then transferred to a Zeta-probe membrane (Bio-Rad) using the Trans-Blot SD semidry transfer apparatus (Bio-Rad) per manufacturer’s instructions. RNA was UV-crosslinked to the membrane and probed for each given RNA using a 5′ biotinylated DNA oligo of complementary sequence in ULTRAhyb (Ambion) hybridization buffer at 42°C. Blots were developed using the Ambion Brightstar BioDetect kit protocol. Chemiluminescent signals were detected using the ChemiDoc MP imager (Bio-Rad) and image analysis was performed using the Image Lab software v. 6.0.1. Signal intensity for each sRNA was normalized to a control RNA (SsrA). RNA turnover curves and half-lives were generated using GraphPad Prism 8.2, 150 mM KCl and 1 mM TCEP. 3 μl of each sample was applied to glow discharged (EasiGlow Pelco R2/2 Au Ultrafoil grids (Quantifoil)). Excess sample was blotted away with an FEI Vitrobot (IV)  immediately after addition of 8 mM CHAPSO (3-([3-cholamidopropyl]dimethylammonio)-2-hydroxy-1-propanesulfonate). CHAPSO was necessary to prevent the PNPase assemblies from adhering to the air-water interface during grid preparation. After blotting, the grids were vitrified in liquid ethane and screened on a FEI Talos Arctica. All datasets were collected on a FEI Titan Krios equipped with a Gatan K2 camera and the data collection parameters for all specimens are summarized in PNPase, PNPase-sRNA and PNPase-sRNA-Hfq samples were prepared at 8-12 μM in a buffer not supporting catalysis, containing 20 mM Tris-HCl pH 8, 2.5 mM MgClFor apo-PNPase and the PNPase-sRNA constructs, all processing steps were performed in Relion 3.0  and cryoFor apo-PNPase the particles were then subjected to C3 symmetry expansion. The expanded particle set was subjected to focused/masked classification without alignments to better resolve the KH-S1 portal. In parallel polished particles were transferred to cryoSPARC 2.15 and subjected to symmetry expansion and subsequent 3D variability analysis (3DVA) . A schematic overview of the processing pipeline for apo-PNPase is displayed in leuZ is displayed in A schematic overview of the processing pipeline for PNPase-Hfq-3ʹETSCaulobacter crescentus PNPase (pdb-ID 4aim)  (E. coli Hfq was docked in the cryo-EM maps (pdb-ID 1HK9). The 3ʹETSleuZ RNA backbone was traced in Coot  . In the ID 4aim) . An autoID 4aim) , was useID 4am3) . For the in Coot . Ramacha in Coot  and ISOL in Coot . The qua in Coot , which u in Coot . Images  in Coot . The staNorthern Blots  were quaRNA degradation was quantified by recording of the fluorescence of RNA bands resulting from RNA degradation by PNPase/RNase E/RNase III on the urea PAA gel  and comparing it to the internal standard. RNA turnover curves based on the mean and standard deviation of 3 independent assays were generated using GraphPad Prism 8.


The Coronavirus (COVID-19) pandemic struck global society in 2020. The pandemic required the adoption of public policies to control spread of the virus, underlining the mobility restrictions. Several studies show that these measures have been effective. Within the topic of Coronavirus spread, this original paper analyses the effect of mobility on Coronavirus spread in a heterogeneous regional context. A multiple dynamic regression model is used to control sub-national disparities in the effect of mobility on the spread of the Coronavirus, as well as to measure it at the context of Spanish regions. The model includes other relevant explanatory factors, such as wind speed, sunshine hours, vaccinated population and social awareness. It also develops a new methodology to optimise the use of Google trends data. The results reveal heterogeneity among regions, which has important implications for current and future pandemic containment strategies. On 11 March 2020, the World Health Organization (WHO) declared the emergency caused by the outbreak of a new Coronavirus (COVID-19) to be an international pandemic. Previously, Asian countries such as China (particularly the Wuhan region), South Korea and Singapore had been severely affected by the Coronavirus, necessitating actions to contain its spread. By early March 2020, Italy (with the outbreak in Lombardy) was the only European country that had applied restrictions. Subsequently, most Western countries applied more severe restrictions to contain spread. Spain, France, Germany, the UK, the USA, and many others applied new restrictions, the strictest being home confinements. These policies were extended throughout 2020 and 2021, with continuous changes due to the different waves and being reduced gradually as vaccination has progressed until the last months of 2021. In addition, restrictions have varied over time, including perimeter closures, time restrictions, capacity reductions or closure of certain areas.The aim of these policies was to increase social distancing and reduce the personal contact responsible for Coronavirus spread , 2. One Various authors have analysed the mobility restrictions that most Western governments used to contain the pandemic. Studies follow three different lines that are closely related but use different methodologies and measures. The first line examines the effects of mobility restrictions on evolution of Coronavirus spread, focussing on lockdown policies , 4, 6.1 Socioeconomic, physical or biological studies of the factors that determine spread of the illness have focussed on analysing individual countries , 10–13, In this way, the novelty of this paper is to control sub-national disparities in the effect of mobility on the spread of the Coronavirus, as well as to measure it. Moreover, it includes the variable of vaccinated people in the analysis.The study focuses on Spanish regions for three main reasons: the high incidence of COVID-19 in Spain, the high level of decentralisation and thus regional heterogeneity,The factors that explain the spread of Coronavirus can be grouped into the following four groups: mobility, deeply related to social distancing; social awareness, environmental aspects and other factors.Concerning the first group of factors, different authors have analysed the impact of human mobility and economic activity on the spread of viral diseases before the Coronavirus pandemic , 18 and The main conclusion of previous research on this topic is the need for public action, involving mobility restrictions, to contain the spread of any viral disease that constitutes a special potential danger for society. A few studies of mobility restrictions and lockdowns in different parts of the world support this conclusion in the case of the Coronavirus , 12, 19.With respect to the first country affected, China, various works on issues such as the Wuhan lockdown reach essentially the same conclusion. Mobility restrictions are effective if the key aim is to contain Coronavirus spreadResearch of Italy and China reach very similar conclusions. Mobility plays a central role in the spread of Coronavirus in Italy’s regions, as do other factors, such as temperature, air pollution and nearness to outbreak points . Other aAs abovementioned, the Coronavirus pandemic has had a global impact, but it has struck some countries harder than others. Although China was the first country affected, it was not ultimately the hardest hit. The US, the UK, Italy, and Spain were the countries most affected during the first stage. Later, other countries as Brazil or India were harder hit. The greater severity of the pandemic in these countries can be explained by social and institutional factors, such as a higher proportion of elderly people, employment in the service sector and globalisation  and the The analysis of the datasets of five large cities in the US shows striking differences among cities in the effect of mobility reduction on the decline in cases per capita. New York City is the most significant case, and lockdown policies again play an important role . BonaccoThere are two reasons for these omissions. The first reason involves both the use of cities, a different concept than the region, and the use of different measures of mobility and variables for each city. This approach prevents researchers from isolating the effect of mobility. The second reason is not measuring the impact of mobility on Coronavirus spread in each region. This occurs because the study does not establish the relationship but only the impact of mobility restrictions or calculates the average impact for all regions.Regarding the second groups of factors, Milani  and TiwaGoogle Trends enables measurement of the population risk perception by selecting any terms closely related to the pandemic. This indicator of social awareness may be more accurate than official new cases or deaths, which are an imperfect measure . FantazzMost existing research examines the impact of fear on the stock market and financial economy. This research demonstrates that an increase in Google searches with different terms related to COVID-19  is significantly and negatively associated with variations in stock market prices –28. It aA common and relevant aspect in the literature discussed in the preceding paragraphs is the study of early phases of the pandemic. In these initial phases, the lack of knowledge about the Coronavirus was remarkable, thus, the effects of Social Awareness should become less important over time and even disappear.With respect to the third group of factors, several studies analyse weather conditions, such as temperature , humiditOther works include sunshine hours as an alternative factor to explain the Coronavirus spread , 34. MorThe last analysed factor is the wind speed, which increases the number of cases and deaths . The impConcerning the last group of factors, some studies analyse issues that are related to society and institutions, diagnostic capability, or vaccination process. Concerning socioeconomic and institutional factors related to Coronavirus spread, population density , 2, eldeFinally, the vaccination process, has been examined to a lesser extent due to its recent onset. Previously to the start of the vaccination process, two main groups of studies can be identified. First, some authors study issues, such as the herd effect, showing the risk inherent to the strategies that seek it as main goal  or the nThe literature review suggests the significance of various factors in Coronavirus spread. After analysing these factors, empirical analyses were performed to test their incidence in Spain from a regional perspective , 40.Reported cases of COVID-19 per 1,000,000 inhabitants between 15 March 2020 and 15 November 2021 . Sample 7Mobility habits collected between 15 March 2020 and 15 November 2021  describ.Search interest of the term “Coronavirus” as measured by Google searches  between Sunshine hours in a day  collecteWind speed (daily average)  between Percentage of the population vaccinated  between A pool data with 10353 observations and 17 regions during a period of just over 22 months was created using daily data. The pooled data provided a more complete database and enabled control of individual heterogeneity and more accurate identification of the adjustment dynamics.Dependent variable:As stated above, one aim of this paper is to investigate the influence of mobility restrictions on Coronavirus (COVID-19) spread during the pandemic. The unit of regional analysis was NUTS 2 for Spain. The data used in the estimates were collected from the following sources:Explanatory variablesMain objective: habitual mobilityOther control variables:Social awareness: captures the search interest of the term “Coronavirus” throughout the analysed period. Google Trends provides a standardised time series, in which the day with the highest relative number of searches takes the value of 100. The regional values are also standardised, assigning the value 100 to the region with the highest relative volume of searches throughout the period. One limitation is that Google Trends API provides weekly or monthly rather than daily data for periods longer than 3 months. This limitation makes it impossible to obtain daily panel data for series of longer than 3 months, greatly reducing the utility of this data source.Coronavirus spread: measured by reported cases of COVID-19 per 1,000,000 inhabitants.In view of the foregoing, this paper develops a new methodology to overcome this limitation by combining three processes. First, quarterly regional data are panelised using Coello  repositoSun: measured as the average of the sunlight hours of all the meteorological stations collected in AEMET  for eachWind speed: measured as the average of the wind speed of all meteorological stations collected in AEMET  for eachVaccination: measured by the percentage of vaccinated population .Region: dummy variable for each of the 17 analysed regions.It means a relevant methodological contribution, which provide valuable tools for future studies that use Google Trends as an information source. The process developed here to obtain a daily data pool for periods longer than 3 months enables the use of Google searches in many fields of knowledge for long periods, extending the study by Narita and Yin .Sun: meaThe goal of this study is to estimate the effect of mobility on spread of the Coronavirus in a geographical area of regional scope. Thus, the study aims to examine, not only to control, the magnitude of possible regional heterogeneity. This goal requires using parametric estimation. Among the feasible alternatives, linear parametric estimation is the most appropriate because it is easy to understand and interpret, and because it fits more complex nonlinear specifications well.i refers to the region  .1111Because this is a daily sample, the Durbin Watson Test is used to detect possible self-correlation problems.The results of estimating Eq.  using diThe variable mobility habits was estimated independently for each region, and globally for all the regions (variables Mobility Habits), in both models to obtain each regional effect. Thus, the estimated coefficients for each region must be added to the overall effect. To avoid multicollinearity, one region  has been omitted, with its estimated effect corresponding to that of the global variable. The other variables were estimated jointly for all regions.In both estimations, mobility habits  is positively related (in most regions) to Coronavirus spread after 14 days. For example, in Aragon, an increase in mobility habits of one percentage point  10 days later. These values establish a inverse relationship, as expected and in line with other studies  but not An increase in Sun of one daily sunlight hour induces a decline  of 0.815 cases per 1,000,000 inhabitants 14 days later. If wind speed increases 1 km/h the severity of the pandemic decreases by 0.262 cases 1,000,000 inhabitants 14 days later, being this not significant.If population vaccinated increases by one percentage point, the new cases 44This paper analyses the heterogeneous spread of Coronavirus in Spanish regions. To study the relationship between mobility and Coronavirus spread, mobility was measured by number of people who leave their geographic area, understood as the surrounding area inhabited by 5000 people. This mobility is closely related to the lockdowns decreed by Spanish regions at different stages of the pandemic, measures that attempt to contain the pandemic and reduce cases. This research found that these measures do not have the same effect in all regions, as the relationships between nearby areas differ greatly.The analysis shows the heterogeneous effect of Coronavirus on Spanish regions. This paper confirms that daily new Coronavirus cases are directly related to mobility habits 14 days before. Other issues, such as social awareness, weather factors and vaccinated population, are also relevant in explaining Coronavirus spread. This paper also considers the percentage of vaccinated people as a relevant factor in explaining the Coronavirus spread. The inclusion of this key aspect means a step beyond previous studies. Specifically, the high significance of the percentage of vaccinated people in reducing the number of new infections is confirmed. It should be noted that Spain is among the countries with the highest vaccination rates.The policy implications of these heterogeneous effects suggest applying different measures at regional level. Then, establishing mobility restrictions in the NUTS of central Spain would have a stronger effect. During the first stage of restrictions (March–June 2020), the same measures were applied throughout Spain. Afterwards, different levels of de-escalation were applied based on other criteria, such as population size. Later, other restrictive policies  were applied with the same objective. Subsequently, the measures were primarily decided and applied at the regional level, allowing governments to tailor their policies better to regional specificities.The main limitations of this research involve the availability and quality of the data. More granular regional data were needed for mobility areas.Finally, analysing the implications of heterogeneous context for restrictive policies at different regional and local levels requires further investigation. Future research could also extend this study to develop new modelling that includes more territorial variables to control for spatial heterogeneity.


Early decline in ovarian function known as premature ovarian aging (POA) occurs in around 10% of women and is characterized by a markedly reduced ovarian reserve. Premature ovarian insufficiency (POI) affects ~1% of women and refers to the severe end of the POA spectrum in which, accelerated ovarian aging leads to menopause before 40 years of age. Ovarian reserve refers to the total number of follicle-enclosed oocytes within both ovaries. Oocyte DNA integrity is a critical determinant of ovarian reserve since damage to DNA of oocytes within primordial-stage follicles triggers follicular apoptosis leading to accelerated follicle depletion. Despite the high prevalence of POA, very little is known regarding its genetic causation. Another little-investigated aspect of oocyte DNA damage involves low-grade damage that escapes apoptosis at the primordial follicle stage and persists throughout oocyte growth and later follicle development. Senataxin (SETX) is an RNA/DNA helicase involved in repair of oxidative stress-induced DNA damage and is well-known for its roles in preventing neurodegenerative disease. Recent findings uncover an important role for SETX in protecting oocyte DNA integrity against aging-induced increases in oxidative stress. Significantly, this newly identified SETX-mediated regulation of oocyte DNA integrity is critical for preventing POA and early-onset female infertility by preventing premature depletion of the ovarian follicular pool and reducing the burden of low-grade DNA damage both in primordial and fully-grown oocytes. Senataxin (Setx) is an RNA/DNA helicase required for multiple DNA processes including transcriptional regulation, the resolution of RNA:DNA hybrids (or R-loops) arising at transcription pause sites and DNA repair . RegardiSETX mutations cause the autosomal recessive neurodegenerative disorder, ataxia with oculomotor apraxia type-2 (AOA2). AOA2 belongs to a group of rare autosomal recessive cerebellar ataxias (ARCAs), which also include Friedreich ataxia and ataxia-telangiectasia , a form of juvenile ALS characterized by limb weakness, severe muscle wasting, normal sensation, and pyramidal tract signs , were shown to decline with aging in oocytes and, importantly, restoring oocyte NAD+ reserves by feeding of an NAD+ precursor could rejuvenate oocytes and restore fertility in older females (+ in turn regulates oxidative stress in oocytes at least in part via a family of NAD+-dependent deacetylases and deacylases known as sirtuins (SIRT1-7); oocytes from mice over-expressing SIRT2 exhibit delayed aging associated with reduced ROS  or homozygous (SETX−/−) deletion of SETX. We found that at young ages, neither follicle-enclosed oocytes within ovaries nor isolated fully-grown oocytes from SETX mutants exhibited increased DSBs compared with wild-type mice , which is counteracted by Cdc25 phosphatases (Maintenance of G2-arrest during the oocyte’s protracted prophase arrest (lasting up to 4–5 decades in humans) therefore revolves around preventing Cdk1 activation. This occurs phatases . Criticaphatases . Hence, Oocytes within follicles experience strong Cdk1 suppression due to Wee1B-mediated inhibition, which is further reinforced by inherently low levels of Cdk1 and cyclin B1 in incompletely grown oocytes . Oocytesvia the DNA damage response (DDR), which delays entry into M-phase thereby enabling DNA to be repaired  and prevents chromosome mis-segregation by delaying anaphase-onset in the presence of chromosomes that have not become properly attached to spindle microtubules  occurs over prolonged periods throughout the individual’s lifetime, it is highly implausible for an oocyte to be completely free of damage throughout its entire growth phase within ovarian follicles in vivo and then to suddenly acquire very severe damage only at the very transient period when ovulation is about to occur. Previous experimental models involving short-term in vitro treatment of DNA-intact fully-grown oocytes  and surprisingly found that all reproductive parameters – oocyte DNA damage, follicle numbers, follicle atresia, numbers of fully-grown oocytes, oocyte maturation, and litter sizes – in 8-month-old SETX+/− females were equally impaired as in 8-month-old SETX−/− females , a condition characterized by high ovarian reserve (SETX gene was disrupted by a single mutation – a deletion of exon 4 – which resulted in a complete absence of Setx protein in knockout animals (Investigating the role of isorders . It is t reserve . We note reserve  whereas  animals .SETX mutations can induce a POA phenotype. Based on the variability in neurological disease profile produced by different SETX mutations in humans, it may well be that only a fraction of mutations results in POA. Identifying which SETX mutations are linked with POA in women will be an important future undertaking.Premature ovarian aging remains an enigmatic condition with very few known genetic causes. Very recent studies in the mouse model suggest that The author confirms being the sole contributor of this work and has approved it for publication.HH is a co-founder, shareholder, and advisor of Jumpstart Fertility Inc., which was founded to develop research into NAD+-dependent pathways involved in female fertility.


Semen induces mucosal changes in the female reproductive tract to improve pregnancy outcomes. Since semen‐induced alterations are likely short‐lived and genital inflammation is linked to HIV acquisition in women, we investigated the contribution of recent semen exposure on biomarkers of genital inflammation in women at high HIV risk and the persistence of these associations.We assessed stored genital specimens from 152 HIV‐negative KwaZulu‐Natal women who participated in the CAPRISA 008 trial between November 2012 and October 2014. During the two‐year study period, 651 vaginal specimens were collected biannually (mean five samples per woman). Cervicovaginal lavage (CVL) was screened for prostate‐specific antigen (PSA) by ELISA, whereas Y‐chromosome DNA (YcDNA) detection and quantification were conducted by RT‐PCR, representing semen exposure within 48 hours (PSA+YcDNA+) and semen exposure within three to fifteen days (PSA−YcDNA+). Soluble protein concentrations were measured in CVLs by multiplexed ELISA. T‐cell frequencies were assessed in cytobrushes by flow‐cytometry, and vulvovaginal swabs were used to detect common vaginal microbes by PCR. Linear mixed models adjusting for factors associated with genital inflammation and HIV risk were used to assess the impact of semen exposure on biomarkers of inflammation over multiple visits.p = 0.046) and CD4+HLA‐DR+ T cells  respectively. PSA detection was specifically associated with raised pro‐inflammatory cytokines , and with the detection of BVAB2 , P. bivia  and Gardnerella vaginalis .Here, 19% (125/651) of CVLs were PSA+YcDNA+, 14% (93/651) were PSA−YcDNA+ and 67% (433/651) were PSA−YcDNA−. Semen exposure was associated with how often women saw their partners, the frequency of vaginal sex in the past month, HSV‐2 antibody detection, current gonorrhoea infection and Nugent Score. Both PSA detection (PSA+YcDNA+) and higher cervicovaginal YcDNA concentrations predicted increases in several cytokines, barrier‐related proteins  and activated CD4+CCR5+HLA‐DR+ T cells (β = 0.050; CI 0.001 to 0.098; More recent semen exposure was associated with raised levels of inflammatory biomarkers and the detection of BV‐associated microbes, which declined by three to fifteen days of post‐exposure. Although transient, semen‐induced alterations may have implications for HIV susceptibility in women. HBiomarkers that detect semen within vaginal specimens may be beneficial to characterize the effects of semen exposure on female genital inflammation and HIV risk. Prostate‐specific antigen (PSA) and Y‐chromosome deoxyribonucleic acid (YcDNA) detection are well‐characterized biomarkers of semen exposure , 17, 18.Considering the transience of semen‐associated immune alterations in the FGT , 22, a p22.1We enrolled 152 HIV‐negative women between 20 and 44 years of age from KwaZulu‐Natal who participated in the CAPRISA 008 study , 24, 25.2.22.2.1The Human PSA‐total ELISA Kit  was used to detect PSA in CVL supernatants according to the manufacturer’s protocol. Briefly, 100 µL of samples, standards and negative controls were examined in duplicate. The CVL specimens were considered PSA positive if detectable concentrations were above the lowest standard’s average concentration. Absorbance was measured at 450 nm with a VersaMax™ ELISA Microplate Reader. Detection of PSA within vaginal specimens indicated semen exposure within 48 hours before genital sampling.2.2.2PrecisionFAST™ Mastermix were used according to the manufacturer's instructions (PrimerDesign Ltd). Amplification was conducted on the Applied Biosystems® QuantStudio™ 5 real‐time (RT)‐PCR System . Detection of YcDNA within vaginal specimens indicated semen exposure within 15 days before genital sampling . Co. Co28]. 2.2.4Multiparametric flow cytometry was used to assess the expression of activation markers (CD38+ or HLA‐DR+), the maker of proliferation (Ki67+) and the HIV co‐receptor (CCR5+) on CD4+ T cells in cervical cytobrush‐derived specimens. The viability of cervical mononuclear cells (CMCs) was determined using the LIVE/DEAD™ Fixable Dead Cell Staining Kit  as outlined in the manufacturer's protocol. CMCs were treated with antibody‐conjugated fluorophores, washed and fixed Table . Data we2.2.5® assays . Mu. Mu29]. ® assays .2.2.6Statistical analyses were performed using GraphPad Prism version 8.4.3 , STATA version 15.0  and SAS version 9.4 . Continuous variables and proportions were compared at baseline using the Kruskal–Wallis test and the chi‐square or Fisher’s exact test respectively. Longitudinal analyses included one model with YcDNA concentrations as the main exposure variable and a complementary model with PSA/YcDNA categories as the main exposure variable. CVL specimens were classified in terms of PSA and YcDNA detection as PSA−YcDNA−, PSA+YcDNA+ and PSA−YcDNA+. The Mann–Whitney test was used to determine whether YcDNA concentrations differed significantly between PSA+YcDNA+ and PSA−YcDNA+ specimens at baseline. Receiver operating characteristic (ROC) curve analysis was used to plot the lowest cut‐off YcDNA concentration that predicted PSA positivity. Linear regression models were used to determine the impact of PSA+YcDNA+ and PSA‐YcDNA+ events on MMP/TIMP concentrations compared to PSA−YcDNA− events at baseline. Spearman’s Rank correlation was used to determine the relationship between concentrations of YcDNA and MMPs/TIMPs at baseline. Linear mixed models (LMMs) adjusting for repeated measures were used to assess the impact of PSA+YcDNA+ and PSA−YcDNA+ events on cytokine concentrations and immune cell frequencies compared to PSA−YcDNA− events over multiple visits. Generalized estimating equation (GEE) models using a logit link were used to compare microbe presence between PSA+YcDNA+, PSA−YcDNA+ and PSA−YcDNA− groups over multiple visits. Multivariable LMMs adjusted for the contribution of study arm (CAPRISA or family planning clinics), time in the study, Nugent Score, participant age, STIs, the frequency of vaginal sex in the past month, and genital inflammation status . The Ben33.1p = 0.038), the frequency of vaginal sex in the past month (p = 0.006), Herpes simplex virus (HSV)‐2 detection (p = 0.047), current gonorrhoea infection (p = 0.018) and Nugent Score (p = 0.003). Higher median Nugent Scores were specifically driven by semen exposure within 48 hours compared to no semen exposure (median 3 (IQR 1 to 7) vs. median 1 (IQR 0 to 3), respectively, p = 0.003). Furthermore, women with evidence of semen exposure within three to fifteen days reported more frequent acts of vaginal sex in the last month than women with no evidence of semen exposure (median 8 (IQR 4 to 10) vs. median 4 (IQR 2 to 6), respectively, p = 0.017).Baseline clinical and demographic data are reported for 137/152 women with both PSA and YcDNA data available  of YcDNA+ specimens (i.e. PSA+YcDNA+ and PSA−YcDNA+ specimens) had a yield sufficient for quantitation. Women with detectable genital PSA  had significantly higher YcDNA concentrations than women without  vs. 0.002 ng/µL (0.002 to 0.017) respectively; Since higher YcDNA concentrations were observed soonest after semen exposure, it suggests a potential for a threshold YcDNA concentration to serve as a proxy for the timing of semen exposure before genital sampling. ROC curve analysis suggests a YcDNA concentration cutoff of 0.005 ng/µL predicts PSA positivity with the greatest sensitivity  and with a specificity of 62.3%  and VEGF , both maintaining statistical significance after FDR adjustment.Since semen’s impact on the FGT is likely short‐lived , 22, we p < 0.001). In comparison, PSA−YcDNA+ specimens only had increased concentrations of IP‐10  and IL‐3 .Cytokine concentrations were also compared between PSA+YcDNA+ specimens (n = 124) and PSA−YcDNA+ specimens (n = 93) relative to PSA−YcDNA− specimens (n = 433) over multiple visits. PSA+YcDNA+ events were significantly associated with increases in 18/48 cytokines and with reductions in two cytokines relative to PSA−YcDNA− events Figure . The str3.4p = 0.024), TIMP‐1  and TIMP‐4 , TIMP‐1  and TIMP‐4  had higher concentrations of MMP‐2  was associated with higher frequencies of activated HIV target cells  = 0.269; CI 0.095, 0.764; p = 0.014; Figure Since vaginal microbial diversity is associated with HIV infection in women , 7, we ep = 0.015), P. bivia , G. vaginalis  and reduced detection of Lactobacillus jensenii .Semen exposure within 48 hours  was associated with more frequent detection of BVAB2  before genital sampling.Semen exposure within 48 hours and higher YcDNA concentrations were associated with raised levels of several cytokines, whereas semen exposure within three to fifteen days was associated with increased concentrations of only two cytokines (IL‐3 and IP‐10). Although transient, elevated concentrations of IL‐6, TNF‐α, IP‐10, RANTES and IL‐10 associated with more recent semen exposure have also been related to increased HIV risk in women , 32. Of Our findings confirmed that more recent semen exposure was also associated with increased frequencies of activated endocervical CD4 T cells (CD4+HLA‐DR+ and CD4+CCR5+HLA‐DR). Studies suggest that semen exposure at the FGT is associated with an initial pro‐inflammatory response resulting in leucocyte recruitment to remove excess and abnormal sperm , 36. ThiG. vaginalis. Further studies are required to determine reasons for this association, for example, the contribution of semen‐derived antimicrobial activities, the impact of semen on G. vaginalis growth dynamics, etc. Conversely, semen exposure within 48 hours was associated with increased detection of several BV‐associated microbes  and reduced detection of L. jensenii, whereas women exposed to semen within three to fifteen days only had an increased detection of P. bivia in vaginal specimens. Studies have demonstrated that a diverse vaginal microbiome with increased Prevotella and reduced Lactobacilluscrispatus is associated with a higher risk of HIV acquisition among women [Pathogens, STIs and commensal microbes present in semen and at the male genital tract , 38, 39 ng women , 7. Thisng women , 7.et al. [A strength of this study was the use of recent semen biomarkers and the wealth of immune and microbial data to reliably assess the effect of semen exposure on the female genital mucosa over multiple visits. To our knowledge, this is the first study to assess the impact of YcDNA concentrations and the timing of semen exposure on markers of genital inflammation related to HIV risk in women. Given that semen itself contains several endogenously produced cytokines and CD4+ T cells from the male partner , 41, 42,et al. , demonst5This longitudinal study demonstrates that semen exposure induces a transient pro‐inflammatory immune response at the FGT which may significantly impact HIV risk in women. Here, PSA detection and higher concentrations of YcDNA, both indicative of recent semen exposure, were associated with increases in cervicovaginal cytokines and barrier‐related proteins, recruitment, and activation of endocervical CD4 T cells and alterations in vaginal microbes. These findings emphasize the need for studies of genital mucosal immunity to STIs such as HIV to consider the contribution of semen exposure to the FGT immune and microbial environments, preferably using a biomarker of recent semen exposure. This study also highlights the importance of consistent condom use, particularly in settings where women are at increased risk of acquiring HIV.The authors declare that they have no competing interests.J.J., S.N. and L.J.P.L. contributed to the conception and design of the study. J.J., L.J.P.L., A.M., M.F. and R.S. performed the experiments. J.J., L.J.P.L. and F.O. analysed and interpreted the data. J.J. and L.J.P.L. wrote the manuscript. All authors have read and approved the final manuscript.Table S1. List of cytokines measured in cervicovaginal lavage supernatant specimensTable S2. Flow cytometry information on the antibody clones, fluorophores, and suppliersTable S3. List of common STI pathogens and other vaginal microbes measured in vulvovaginal swabsTable S4. Sensitivity and specificity for the YcDNA concentration cutoff value of 0.005 ng/µLFigure S1. Graphical representation of the data available at baseline and longitudinally for CAPRISA 008 study participants.Figure S2. ROC curve for all YcDNA concentration cutoff values.Click here for additional data file.


In this study, the influence of several key elements of the cytologic sample workflow on DNA and RNA content was evaluated.The A549 cell line, patient-derived organoids, and pleural effusions were used to investigate the effect of (1) several collection media and delayed time to processing; (2) cytology specimens; (3) cytologic staining; and (4) formalin-fixed, paraffin-embedded (FFPE) cell block processing on nucleic acid quality and quantity as determined by fragment analyzer, Qubit analysis (Thermo Fisher Scientific), and quantitative polymerase chain reaction–based analysis on the Idylla platform (Biocartis).Alcohol-based collection media (CytoRich Red [Thermo Fisher Scientific] and EtOH95%) displayed high DNA and RNA preservation capacity, while phosphate-buffered saline and, to a lesser extent, formalin were associated with high RNA quality. Cytospin and smear cytology specimens were subject to DNA and RNA loss. Cytologic staining had no further impact on sample quality, hence destaining is not necessary. Both H&E-stained and unstained FFPE sections are compatible with nucleic acid analysis, despite a strong decrease in DNA and RNA quality.Although several key elements of the cytologic sample workflow have an influence on DNA and RNA quality and quantity, the selection of these elements is also dependent on the downstream (ancillary) testing methods. Key PointsIn lung cancer, cytologic samples are often the only source of material for molecular diagnostic testing. There are few studies on the influence of cytologic sample processing on DNA and RNA quality and quantity.Downstream (molecular) analyses largely determine the type of cytologic sample processing.Cytologic  or H&E-stained samples were found to be compatible with fluorophore-based analysis. Hence, there is no need to destain samples.1 The discovery of actionable oncogenic driver alterations combined with approved targeted therapies have significantly improved outcomes for patients with advanced-stage non–small cell lung cancer (NSCLC).2 It is currently standard practice in metastatic NSCLC to test for oncogenic drivers and biomarkers for immunotherapy—namely, EGFR alteration; ALK, ROS1, and RET rearrangements; MET amplification and MET exon 14 skipping; BRAF V600-sensitizing alteration; and programmed cell death 1 ligand 1 (PD-L1) expression.3 Recently, screening for NTRK fusions has also been included in the European Society for Medical Oncology recommendations.4 In many cases, only cytologic material is available for diagnostic, prognostic, and predictive assessment.5 There is wide variety in cytologic sample preparations and preanalytical factors, and their influence on the nucleic acid content is unclear. The College of American Pathologists (CAP) has developed a clinical practice guideline and recommendations for clinicians and pathologists on how to collect and process cytologic samples for ancillary testing.6 They graded their recommendations by the strength of the evidence because in some cases they were hampered by the paucity of high-quality studies on the computability of cytologic sample processing and ancillary testing. Furthermore, they took only DNA-based molecular testing into account, while RNA analysis may be better suited to fusion detection.4Lung cancer is the most common malignancy and the leading cause of cancer-related death.In this study, the impact of several key elements of the cytologic sample workflow on DNA and RNA quality and quantity was evaluated, including collection media combined with delayed time to processing; different cytology specimens (cytospin and smear) and stains; and formalin-fixed, paraffin-embedded (FFPE) cell block processing. A lung cancer cell line, patient-derived organoids (PDOs), and pleural effusions (PEs) were used to obtain clinically relevant results. Remarkable differences were observed in sample quality; it was also noted that the choice of the preanalytical variables is subject to the downstream ancillary testing method.In this study, using a lung cancer cell line, 2 PDOs and leftover material of exudative PEs, the influence of several variables of the cytologic sample workflow on the quality and quantity of the genetic material was evaluated. In case of the PDO cell lines and PEs, ethical committee approval (20/06/059) was obtained. The study was conducted according to the Declaration of Helsinki.2 in a humidified incubator at 37°C. Cell cultures were regularly evaluated for the absence of mycoplasma contamination using the MycoAlert Mycoplasma Detection Kit (Lonza). Upon reaching an 80% confluence rate or higher, cells were harvested for downstream experiments by treatment with 0.25% trypsin for 5 minutes. Cells were resuspended in supplemented DMEM and centrifuged for 5 minutes at 450g . The supernatant was removed, and cells were resuspended in 1% phosphate-buffered saline (PBS). Cell counting (with trypan blue) was performed in triplicate using the TC20 Cell Counter (Bio-Rad).The human lung cancer cell line A549, purchased from the American Type Culture Collection, was cultured as monolayers in Dulbecco’s Modified Eagle Medium , supplemented with 10% fetal bovine serum (Life Technologies), 1% penicillin (100 U/mL)/streptomycin , and 2 mL L-glutamine . Cells were maintained in exponential growth phase at 5% CO7 with some minor alterations. The PDOs were collected from an established PDO cell line. For passaging, they were digested to single cells using TrypLE Express (Gibco). Afterwards, they were resuspended in Advanced DMEM/F12 medium supplemented with 1% GlutaMAX (Gibco), 1% penicillin/streptomycin, and 1% HEPES , which in turn was supplemented with 10% Noggin-conditioned medium, 10% R-sponding-1-conditioned medium, b27 without vitamin A (Gibco), 10 mmol/L nicotinamide (Sigma-Aldrich), 25 ng/mL FGF-7 (Peprotech), 100 ng/mL FGF-10 (Peprotech), 500 nmol/L A83-01 (Tocris), and 5 µM Y-27632 . Single cells were embedded in basement membrane matrix  and seeded on a preheated plate. After polymerization, the embedded cells were overlaid with the supplemented ADF+++ to facilitate organoid formation. Upon reaching a sufficient number of organoid-filled domes (confluence of 80% after 12-14 passages), the PDOs were harvested for downstream experiment by digesting them to single cells using TrypLE. They were resuspended in the supplemented ADF+++ and centrifuged for 5 minutes at 450g. The supernatant was removed, and cells were washed in PBS. Cell counting was performed in triplicate using the Cell Scepter .The PDO cell lines were cultured according to the protocol of Dijstra et alg. The supernatant was removed, and cell pellets were combined and washed with PBS. The TC20 Cell Counter was used for cell counting. Threshold settings were adapted to exclude RBCs.Leftover material from exudative PEs of patients with lung cancer was collected in 50 mL conical centrifuge tubes  and centrifuged for 5 minutes at 450g . The supernatant was removed, and the cell pellet was either immediately snap-frozen or used for downstream experiments.Cell suspensions of 200,000 cells per sample were prepared (unless otherwise specified). Samples were centrifuged for 5 minutes at 450The focus of this study was to evaluate key elements of the cytologic sample workflow necessary to obtain adequate material for diagnostic testing.8-10 a questionnaire data set, and considerations based on the new European regulation 2017/746 on in vitro diagnostics medical devices—namely, PBS, formaldehyde 4% buffered solution , ThinPrep CytoLyt Solution (Hologic), CytoRich Red preservative (Becton Dickinson), and ethanol solutions of 40% and 95% ethanol . The 72-hour delay in processing was selected to allow for samples left over the weekend.As the first step after sample collection, several preservatives combined with a 72-hour delay in processing were evaluated on their compatibility with molecular analyses. In total, 6 collection media were selected based on literature review,g. The supernatant was removed, and the cell pellet was resuspended in PBS. Samples were centrifuged again, and the supernatant was removed. The cell pellet was snap-frozen in liquid nitrogen and stored at –80°C until nucleic acid isolation and analysis. All samples were processed in duplicate. Additionally, reference samples, consisting of cell pellets immediately snap-frozen after cell collection, were included.We added 1 mL of collection medium to the cell pellet. Samples were left at room temperature for 72 hours before centrifugation for 5 minutes at 450g . Afterwards, the samples were air-dried for up to 30 minutes and snap-frozen.Next, the adequacy of cytologic specimens  for nucleic acid–based testing was evaluated. Smear and cytospin specimens were compared with the reference samples. In case of smears, cell pellets were resuspended in approximately 10 µL PBS and pipetted onto a coated glass slide . The samples were air-dried for up to 30 minutes before snap-freezing and storage at –80°C. Cytospin specimens were prepared by resuspending the cell pellets in approximately 300 µL PBS. The cytocentrifuge chamber was assembled by the sequential alignment of the cytofunnel , a coated glass slide , and slide rack. The cell suspension was transferred into the cytofunnel and centrifuged for 5 minutes at 650The influence of cytologic staining methods on nucleic acid quantity and quality was assessed next. Papanicolaou and May-Grünwald Giemsa (Giemsa) stains were performed on cytospin specimens. The cell monolayer of these specimens will allow for optimal staining. Samples were fixated in CytoLyt for 1 hour before cytospin processing, as described in the section “Cytology Specimens.” Reference samples and CytoLyt-fixated samples (see “Collection Media and Delayed Time to Processing”) were also included. Cytospin specimens were allowed to air-dry for up to 30 minutes and stored at room temperature (RT) until staining. Papanicolaou and Giemsa staining (Sigma-Aldrich) was performed according to the manufacturer’s instructions. Cytospin specimens were air-dried for up to 1 hour before snap-freezing.g, and the supernatant was removed. The cells were resuspended in formalin and incubated for 1 hour at RT. Afterwards, the samples were centrifuged again, and the majority of the supernatant was removed. The remaining supernatants were used to transfer the cell pellet into a mold containing approximately 200 µL or 1.5 mL preheated (60°C) 4% agar in the case of A549 or PE cell pellets, respectively. The mold was placed on a cold plate to allow the agar to solidify. The agar was placed in a cassette and loaded into the Excelsior ES Tissue Processor (Thermo Scientific). Processed paraffin blocks were stored at RT before sectioning. FFPE sections  were made to evaluate the effect of deparaffinization before nucleic acid isolation and H&E staining. For every 4 sections, 2 sections were taken for standard H&E staining.11 One H&E-stained section was used to evaluate cell content, while the other one, together with the remaining 2 unstained sections, was stored at –80°C until further processing.The nucleic acid content of cell block specimens was investigated. Cell pellets consisting of 15 million to 20 million (A549 cell block) or more than 300 million cells (PE cell block) were centrifuged for 5 minutes at 450American Journal of Clinical Pathology online).DNA and RNA were simultaneously isolated from all samples using the QIAamp DNA FFPE Tissue Kit (Qiagen), with some alterations to the protocol. The duration of the incubation steps at 56°C and 90°C were reduced from 1 hour to 15 and 10 minutes, respectively, based on an in-house protocol. In the case of FFPE sections, the original isolation protocol was used. Nucleic acids were eluted in 50 µL RNase-free water and stored at –80°C. The DNA and RNA isolation efficiency of the adapted protocol was compared with the standard protocol and the QIAamp Blood Mini Kit (Qiagen). The latter served as reference for the purification of nucleic acids from fresh samples  cytospin and FFPE specimens was scraped using a surgical scalpel. The scraping was facilitated by wetting the scalpel with lysis buffer. Before scraping, the H&E-stained and 1 of the unstained FFPE sections were deparaffined by subsequently immersing the sections in xylene and EtOH100%.ALK, ERCC3, MET, NTRK1/2/3, RET, ROS1, and TMUB2. By experiment, a fixed amount of total RNA, ranging from 18 ng to 500 ng, was used.The DNA and RNA concentrations of all samples were measured in duplicate using the Qubit 2.0 Fluorometer with the dsDNA HS Assay Kit and the RNA HS Assay Kit (Thermo Fisher Scientific), respectively, per the manufacturer’s instructions. Per duplicate sample set, the DNA and RNA integrity of 1 duplicate was evaluated using the HS Genomic DNA 50kb Kit and the HS RNA Kit (15NT), respectively, on the Fragment Analyzer (Applied Biosystems). Each sample was analyzed in duplicate according to the manufacturer’s instructions. Quality metrics were represented by the genomic quality number (GQN) and RNA quality number (RQN). We opted to use 2 GQNs based on the percentage of fragments of at least 10,000 and 200 base pairs (bp), respectively. The DNA and RNA quality of the other duplicate sample was assessed using a prototype version of the Idylla GeneFusion Assay on the Idylla Instrument (Biocartis), which contains 9 RNA targets—namely U test was used to further evaluate the effect between individual elements. Statistical analysis was performed using IBM SPSS Statistics, version 27, software. P < .05 was considered statistically significant. Figures were made in GraphPad Prism 7.The Kruskal-Wallis test was performed to ascertain whether there were significant differences in DNA and RNA quality and quantity between the various key elements of the cytologic workflow themselves and vs reference samples. The Mann-Whitney P = .021). It was found to be significantly lower in samples incubated in formalin vs PBS, CytoLyt, CytoRich Red, and EtOH95% . This difference was less pronounced compared with EtOH40% (P = .059). The DNA concentration of samples incubated in EtOH40% also tended to be slightly lower compared with incubation in CytoRich Red and EtOH95% . The RNA yield tended to vary less among the various collection media (P = .06). RNA concentrations were higher in samples collected in CytoRich Red than in PBS, formalin, and EtOH40% . The difference compared with CytoLyt was minor (P = .059). The RNA concentration of EtOH95% was similar to that of CytoRich Red. DNA quality assessed by Fragment Analyzer was also pooled for statistical analysis (P = .036). No further statistical analysis was performed among the different sample types  because of the limited data points. The DNA quality  of samples stored in PBS or CytoRich Red tended to be higher than in the other collection media across all sample types, except for PDO2. Although no significant differences in RNA quality were observed (P = .071), samples collected in formalin presented higher RQN scores (≥9.75 ± 0.25) across all sample types. A DNA fragment length of at least 200 bp was also retained in all samples and sample types. Sample quality in terms of quantitative polymerase chain reaction (qPCR) amplifiability was also assessed using the Idylla GeneFusion Assay P = .054 and P = .072, respectively). In the case of the PDO2 samples, significant variation was observed (P = .026). The difference was more significant when combining the data of all sample types . The RNA quality of the samples collected in PBS was found to be significantly higher compared with samples collected in CytoLyt, CytoRich Red, EtOH40%, and EtOH95% . No difference could be observed between samples collected in PBS or formalin, and the RNA quality of the latter was also significantly higher compared with EtOH40% (P = .015). The DNA quality was similar among the collection media samples.In a first phase, the influence of several collection media  combined with delayed time to processing on DNA and RNA quality and quantity were evaluated. Significant differences were found in DNA concentration, RNA concentration, and the RNA-to-DNA ratio, which served as an indication of sample quality, between the reference and collection media samples in all cell types: A549 cell line, both PDOs, and PE. To further evaluate the influence of the various collection media, DNA and RNA yield was normalized to the reference analysis . The GQNP = .06 and P = .05, respectively). Essentially, no statistically relevant difference in RNA-to-DNA ratio was observed (P = .073). The influence of the cytospin and smear processing itself was further investigated by normalizing the yield to the reference. Although the RNA yield of the cytospin specimens was lower compared with smear specimens (P = .016), no differences in DNA yield could be observed. A significant difference in DNA quality  was noted between the reference and cytology specimens (P = .027)  . BecauseP < .001, P = .002, and P < .001, respectively). These differences were also observed among the cytologic staining process samples themselves, except for the RNA concentration . To further evaluate the effect of the cytologic staining process, the DNA and RNA yield was normalized to the reference P = .001 and P = .003, respectively) compared with the reference sample. The DNA and RNA concentration of the stained and unstained cytospin specimens was similar. Only in the case of the Papanicolaou-stained specimen was the DNA concentration lower than its unstained counterpart (P = .037). The DNA and RNA concentration of the CytoLyt-fixated samples was significantly higher than the stained and unstained cytospin specimens . A trend was observed in DNA quality  between the reference and cytologic staining samples (P = .062) , this was no longer observed when the data of the sample types were combined (based on 3 common RNA targets). DNA quality was also similar between the cytologic staining process samples.The steps of cytologic staining were evaluated for potential interference with DNA and RNA analyses. Fragment Analyzer and Qubit data were pooled for statistical analyses. The DNA and RNA concentrations as well as the RNA-to-DNA ratio were found to differ significantly among all samples ( = .062) . No signP = .002, P = .003, and P < .0001, respectively). Quality assessment using the Idylla GeneFusion Assay, however, revealed that the amplification reactions were not impaired in any sample type or specimen Finally, the DNA and RNA quality and quantity of FFPE cell block specimens were evaluated. Because A549 characterizes cell-poor specimens and PE FFPE cell blocks are cell-rich specimens, we opted not to combine the data; thus, no statistical analysis was performed. The yield of unstained paraffin and H&E-stained sections was compared with unstained, deparaffined sections, which served as reference 13 In this study, the influence of several key elements of the cytologic sample workflow on the compatibility of these samples with ancillary testing was investigated. Besides a lung cancer cell line, PDOs and PEs were used to ensure clinically relevant findings.Cytologic samples have found their way in routine molecular testing for the selection of patients who may benefit from targeted therapy. Originally, guidelines from the CAP, the International Association for the Study of Lung Cancer (IASLC), and the Association for Molecular Pathology (AMP) recommended using only cell blocks for molecular testing. Several studies, however, as well as evidence from real-world clinical practice have revealed that any cytologic sample with adequate cellularity and preservation can be used for ancillary testing.8 Formalin is one of the most commonly used fixatives for both tissue and cytologic samples as part of the paraffin embedding process and is known to induce methylene bridging of bases and the formation of cross-links.10 The low RNA quality of FFPE sections is partly the result of the relatively harsh conditions of RNA isolation—namely, the proteinase K digestion followed by the heating steps to remove these chemical modifications.14 The cell pellets in this study had not undergone paraffin embedding; thus, the duration of the proteinase K digestion and heating steps has been decreased, resulting in high RNA quality. The lower DNA yields are most likely the result of incomplete removal of the chemical modifications by the adapted isolated protocol rather than the low DNA preservation capacity of formalin. Interestingly, CytoRich Red contains a small percentage (<1%) of formaldehyde, resulting in cross-linking. Dejmek et al15 reported poorer DNA preservation by CytoRich Red compared with CytoLyt, despite both collection media being alcohol based. This behavior was not observed in this study, with CytoRich Red even (slightly) outperforming CytoLyt in DNA and RNA preservation. This discrepancy may be explained by Dejmek et al15 using only cell lines. Furthermore, the DNA yield was determined after cell pellets collected in CytoRich Red were deposited on SurePath PreCoat slides (TriPath Imaging) and stained with H&E or Papanicolaou staining, possibly masking the influence of CytoRich Red itself. EtOH95% was also found to have good RNA and DNA preservation capacity, as noncross-linking alcoholic reagents are known to cause little chemical changes.17 The lower preservation capacity observed in EtOH40% is possibly the result of the minor ethanol percentage combined with the fact that pure water is not an ideal medium for cells. The choice of collection medium will most likely depend on the downstream processing methods and ancillary testing. Despite rather limited evidence, the CAP does recommend collecting cytology samples in formalin,6 the most commonly used fixative for the generation of FFPE (cell) blocks.18 Although FFPE cell blocks can be generated from specimens fixated in alcohol-based collection media, a postfixation step in formalin is typically performed. This step might reduce the quality of the often-limited material even more.10 In case of PCR-based analysis, however, both this study and others17 demonstrate that alcohol-based collection media  may be a good alternative. Because all samples were washed with PBS before snap-freezing and the subsequent nucleic acid isolation, the impact of this agent on isolation efficiency16 was not considered while evaluating the effect of the collection media on DNA and RNA.First, the influence of several collection media  and delayed time to processing was investigated. CytoRich Red was found to preserve the RNA content significantly better than the other collection media. Only samples collected in EtOH95% had a similar RNA yield. Samples collected in formalin had the lowest DNA yield, followed by EtOH40%. In contrast, CytoRich Red and EtOH95% had the highest DNA preservation capacity. The DNA quality of samples collected in CytoRich Red and EtOH95% seemed somewhat higher than the other collection media. This phenomenon was not observed with RNA quality, which was significantly higher in samples stored in PBS and, to a lesser degree, in formalin. The high RNA quality of the latter was surprising because studies have shown higher-quality nucleic acids in noncross-linking alcoholic reagents.19 It is also important to note that no coverslip was used on these specimens. If a coverslip is present, it can be removed by soaking in xylene20 or the “freezer” method.21 This step reportedly has no influence on DNA retrieval, but the effects on RNA are still unknown.In the next phase, the sample quality of cytospin and smear specimens was evaluated. No significant difference in DNA and RNA quantity or quality could be observed between the 2 specimens, but it seems that both had a marked decrease in DNA and RNA concentration compared with the reference sample. It is likely that cells or cell content was lost during collection, despite the use of coated slides and collection via scalpel-blade scraping, which has been shown to yield higher DNA concentrations than cell lifting.22-24 In 2 of those studies, it was found that Papanicolaou-stained specimens had a (slightly) lower DNA yield than their Diff-Quik–stained counterparts,24 and another study demonstrated higher DNA fragmentation in archival (>10 years of age) Papanicolaou-stained specimens.23 Both Diff-Quik and Giemsa are Romanowsky stains, the former being a simplified modification, which may explain the similar findings reported in this study. Papanicolaou and Giemsa contain strong chromophores,25 such as hematoxylin and eosin. No interference with the fluorophore-based Idylla qPCR system was observed because these chromophores are likely not retained in the final eluate. Hence, there is no need to destain these specimens before fluorophore-based analyses.Next, the compatibility of Giemsa- and Papanicolaou-stained slides with molecular testing was evaluated. Samples were collected throughout the cytologic staining process. As seen in the previous section, there was a marked decrease in DNA and RNA concentration of the (un)stained cytospin specimens compared with the reference and the CytoLyt-fixed samples. The DNA yield of Papanicolaou-stained specimens was lower than the Giemsa- and unstained counterparts. No significant differences in RNA concentration or DNA and RNA quality were detected. These data correspond to previously reported findings that Papanicolaou-stained specimens are compatible with DNA-based molecular testing.26 It is likely that the agar was dissolved during the H&E staining process. It was noted that during isolation, the columns of the unstained, deparaffined sections of the PE cell block became slightly clogged, while this was not the case with H&E-stained sections. A possible explanation is that agar is not dissolved completely by the deparaffinization process, allowing it to clot after the 90°C incubation step and capturing or preventing nucleic acids from going through the column membrane. In case of paraffin sections, this was even more substantial because of the presence of both the paraffin and agar, resulting in low DNA and RNA concentrations. Because the PE cell block was extremely cell rich, a larger mold and more agar were necessary to set the cell pellet. Hence, the effect of the H&E staining and the agar itself was observed more clearly in the PE cell block specimens than in the A549 specimens. In contrast, DNA and RNA quality and amplification were similar among all FFPE specimens. The significantly lower RQN and GQN scores of the FFPE samples compared with the other specimens in this study clearly highlighted the DNA and RNA degradation associated with FFPE material.18 Despite this finding, cell blocks remain the cytologic substrate of choice. Ancillary molecular methods, such as fluorescence in situ hybridization and immunohistochemistry (IHC), have been validated on FFPE tissue blocks.27 Cell block is also suggested as a valuable sample type because it allows the performance of multiple IHC markers for diagnostics  and predictive  assessment.28 Several studies indicate that alcohol-based fixated cytology samples  are better suited for PCR-based assessment than FFPE cell blocks,17 but these findings on cytologic stains suggest that the presence of H&E did not hamper analysis with the fluorophore-based Idylla system.Finally, we evaluated the sample quality of FFPE specimens. One FFPE cell block was constituted as a cell-poor (A549) and the other as a cell-rich specimen (PE). The effect of deparaffinization and H&E staining was evaluated by cell block. The DNA and RNA concentrations were higher in H&E-stained sections A549 and PE cell blocks than in the unstained counterparts. This observation was more remarkable in samples from the PE cell block. To make cell blocks, the cell pellets must be held in place. In this study, agar was used. Other agents, such as plasma thrombin, gelatin, and HistoGel, are available, as well.The alcohol-based collection media CytoRich Red and EtOH95% seem to have the highest DNA and RNA preservation capacity, with limited quality decrease. Despite this, these cell pellets as such are rarely used in clinical practice because they do not allow histologic assessment. They are most often processed as cytology specimens or FFPE cell blocks. Processing cytologic samples as cytospin or smear specimen was found to result in a significant decrease of DNA and RNA concentration, most likely because of the procedure of cell collection from both specimens. Interestingly, the cytologic stains Papanicolaou and Giemsa did not further influence DNA and RNA concentration or quality. They were even found to be compatible with fluorophore-based analysis despite containing strong chromophores. In the case of FFPE cell blocks, the use of formalin as collection medium is recommended to avoid an additional fixation step in formalin before paraffin embedding. Despite a strong decrease in DNA and RNA quality, H&E-stained and unstained (with or without deparaffinization) FFPE sections were found to be compatible with nucleic acid analysis. Ultimately, the selection of preanalytical variables is largely dependent on downstream ancillary testing.aqab121_suppl_Supplementary_MaterialClick here for additional data file.