Lab Matters Fall 2023 | Page 70

APHL 2023 POSTER ABSTRACTS

Verification of the Qsight 225 MDTM for the Screening of X-linked Adrenoleukodystrophy ( X-ALD ) and Adenosine Deaminase Severe Combined Immunodeficiency ( ADA-SCID ) in Alabama

D . Fang , E . Fontain , D . Kennedy , A . Williams and S . Massingale ; Alabama Department of Public Health , Bureau of Clinical Laboratories

Across the United States , newborn screening ( NBS ) programs test the newborn population for the presence of rare genetic and metabolic diseases every day . State NBS programs will choose which conditions to include on their panels based on the recommended uniform screening panel ( RUSP ). Of the RUSP conditions screened for by the Alabama NBS program , many are identified via tandem mass spectrometry . Having previously used the NeoBaseTM kit on the Waters AcquityTM Tandem Quadrapole Detector ( TQD ), a verification study is being conducted for use of the NeoBase 2TM kit on the QSight 225 MDTM tandem mass spectrometer . In addition to ensuring accurate and precise measurements of analytes for current disorders , this newly verified method will allow for the measurement of key analytes for two new disorders : ADA-SCID and X-ALD . Both X-ALD and SCID are conditions found on the RUSP , however the variant ADA-SCID specifically is not . Out of all instances of SCID , the ADA cases make up approximately 10 – 15 %. As a result of an adenosine deaminase deficiency , there is a toxic build-up of metabolites such as adenosine and 2 ’ - deoxyadenosine , ultimately impacting the immune system in ways that are traditionally observed in pure SCID cases . The NeoBase 2TM kit utilizes these high concentrations of adenosine to allow for the early identification of ADA-SCID . Upon completion of the study , the Alabama Department of Public Health ’ s Bureau of Clinical Laboratories will be able to maintain screening efficiency and expand the state ’ s panel to include the new conditions .

Presenter : Daniel Fang , djfang99 @ gmail . com

NEXT GENERATION / LONG-READ SEQUENCING , METAGENOMICS AND BIOINFORMATICS

A Scalable Model for Metagenomics-based Surveillance for Influenza-like Illness in the Community

R . Stinnett 1 , C . Clark 2 , H . Houdeshell 2 , A . Vest 2 , E . Arnold 2 , K . Broadbent 1 , S . Miller 1 , Robert Schlaberg 1 , M . Hardison 2 ; 1 Illumina ,

2

Aegis Sciences Corporation

The SARS-CoV-2 pandemic accelerated the integration of genomics into pathogen surveillance and demonstrated the value of privatepublic cooperation to scale testing . Commercially available technology could broaden routine surveillance from one pathogen ( SARS-CoV-2 ) to multiple causes of influenza-like illness ( ILI ). This study presents feasibility for community-based ILI surveillance via high throughput next-generation sequencing ( NGS ). Residual , self-collected upper respiratory samples ( n = 4104 ) from individuals across all 50 US States and Puerto Rico seeking SARS-CoV-2 testing at a national retail pharmacy between 2022 Epi Weeks 18 – 46 were tested with the Respiratory Pathogen ID / AMR Panel ( RPIP , Illumina – For Research Use Only . Not for use in diagnostic procedures ) at Aegis Sciences Corporation . RPIP uses target capture-based enrichment for detection , quantification and characterization of 282 pathogens directly from respiratory samples . NGS data were analyzed with the Explify RPIP Analysis app in BaseSpace ( Illumina ), and the results were paired with non-identifying patient demographics and self-reported symptoms . Most participants ( n = 3338 ; 81 %) reported ≥1 respiratory symptom but SARS-CoV-2 was only detected by RT-PCR in 22 % ( n = 740 ). In contrast , RPIP detected respiratory viruses in 55 % ( n = 1856 ) of participants ; SARS- CoV-2 was the most frequently detected virus ( 86 % agreement vs RT-PCR ). Among symptomatic individuals testing negative by RT- PCR ( n = 2583 ), RPIP identified a possible etiology in 1,219 ( 47 %). Viruses detected frequently by RPIP in this group included targets of national viral surveillance , such as influenza A virus subtypes , H3N2 and H1N1 ( n = 120 ; 4 % & n = 19 ; 0.6 %, respectively ), human parainfluenza viruses ( HPIV ) -1 ( n = 12 ; 0.4 %), HPIV-2 ( n = 6 ; 0.2 %), HPIV-3 ( n = 78 ; 2 %) and HPIV-4 ( n = 32 ; 1 %), seasonal coronaviruses ( n = 107 ; 3 %), respiratory syncytial virus ( n = 70 ; 2 %), human metapneumoviruses ( n = 35 ; 1 %), and adenoviruses ( n = 9 ; 0.3 %). Human rhinovirus A ( n = 333 ; 10 %), B ( n = 97 ; 3 %), and C ( n = 117 ; 3 %) were also frequently detected . Notably , RPIP detected viruses that are not routinely tested for influenza C virus or human parechovirus , some of which are of public health concern , e . g ., enterovirus D68 & mumps virus . Genome coverage was sufficient to infer type directly from the sample via the RPIP analysis app in many cases . As bottlenecks to routine implementation of metagenomic NGS are addressed via technical advances , cross-sector collaboration , data standards development and sustained funding & policy support , there is untapped potential to improve understanding of disease on the population level . Scalable sequencing of respiratory samples from symptomatic outpatients seeking testing can improve situational awareness and provide early warning of increased local transmission of pathogens beyond SARS-CoV-2 to inform public health action .

Presenter : Rita Stinnett , rstinnett @ idbydna . com

Comparison of Two Bioinformatics Pipelines for Antimicrobial Resistance Analysis

S . Dar , E . Keller , B . Lee , N . Chapel , P . Stamper , R . Myers ; Maryland Department of Health

Next-generation sequencing ( NGS ) coupled with reliable bioinformatics pipelines is considered essential for surveilling the antimicrobial resistance in healthcare associated infections ( HAI ) of Carbapenem-resistant Enterobacteriaceae ( CRE ). The validation of bioinformatics pipelines is of great importance to ensure consistent findings , which can negatively influence antimicrobial resistance surveillance for patient care . For validation purposes , the comparison of a new bioinformatics pipeline , PHoeNIx ( Portable Healthcare Nextgen Informatics ), was compared against the current Abricate ( github . com , Torsten Seemann ) workflow analyzing antimicrobial resistance markers . The ability of PHoeNIx pipeline to find antimicrobial resistance genes and virulence markers was evaluated while considering user experience ( captured by time for analysis relative to the current workflow ). Parallel evaluation of 138 total isolates were run through both pipelines producing nearly identical results for the five major beta lactam resistance genes blaNDM ( 100 % similarity ( 82 / 82 )), blaVIM ( 100 % similarity ( 2 / 2 )), blaIMP ( 100 % similarity ( 1 / 1 )), blaKPC ( 100 % similarity ( 11 / 11 )), and blaOXA ( 97.2 % similarity ( 72 / 74 ). Of the total isolates