Aerobiologia 20: 99–110, 2004. 2004 Kluwer Academic Publishers. Printed in the Netherlands.
99
The U.S. Government’s right to retain a non-exculsive, royalty free licence in and to any copyright is acknowledged.
Characterization of aerosolized bacteria and fungi from desert dust events in Mali, West Africa Christina A. Kellogg1,*, Dale W. Griffin1, Virginia H. Garrison1, K. Kealy Peak1,3, Nelson Royall1, Raymond R. Smith2 & Eugene A. Shinn1 1
U.S. Geological Survey, 600 4th Street S., St Petersburg, FL 33701, USA; 2Ecole Americane, Porte 36, Rue 111, Badalabougou Ouest, Bamako, Mali, Africa 3 Present address: USF Center for Biological Defense, 3602 Spectrum Blvd., Tampa, FL 33612, USA (*Author for correspondence: E-mail:
[email protected]; Fax: +1-727-803-2031) Recived 14 January 2004; accepted 14 January 2004
Key words: aerobiology, African dust, Bacillus, bacteria, fungi, long-distance transport, Mali, microbiology, Sahara, spores
Abstract Millions of metric tons of African desert dust blow across the Atlantic Ocean each year, blanketing the Caribbean and southeastern United States. Previous work in the Caribbean has shown that atmospheric samples collected during dust events contain living microbes, including plant and opportunistic human pathogens. To better understand the potential downwind public health and ecosystem effects of the dust microbes, it is important to characterize the source population. We describe 19 genera of bacteria and 3 genera of fungi isolated from air samples collected in Mali, a known source region for dust storms, and over which large dust storms travel. 1. Introduction The Sahara/Sahel region of Africa is the Earth’s largest source of aerosolized soil dust (Schu¨tz et al., 1981). It is estimated to contribute as much as one billion metric tons of dust per year to the global atmosphere (Moulin et al., 1997). Satellite images show that African dust is regularly transported west over the Atlantic Ocean to North America, South America and the Caribbean, as well as north across the Mediterranean to Europe. The majority of African dust (30–50% of the total mass) crosses the Atlantic westward to the Americas (Schu¨tz et al., 1981; D’Almeida, 1986), but rare events can send it curving north over the British Isles (Wheeler, 1986) or even Scandinavia (Franzen et al., 1995). The annual variation in exported dust is affected by global climate; it correlates with the North Atlantic oscillation (NAO), which affects atmospheric circulation in the
northern hemisphere and precipitation over North Africa (Moulin et al., 1997). Both the Infra-red Difference Dust Index and the Aerosol Index developed to interpret data from the total ozone mapping spectrometer (TOMS) indicate that the top two sources of African dust are the Bode´le´ Depression near Lake Chad, and a strip covering Mauritania, Mali, and southern Algeria (Prospero et al., 1970; Brooks and Legrand, 2000; Goudie and Middleton, 2001). It is not quite as clear which sources are linked to specific trajectories. However, TOMS satellite images suggest that Mali is one of the source areas for the dust traveling toward North America and the Caribbean (Gillies and Nickling, 1996) (Figure 1). Previous studies in the Caribbean have shown that African dust contains viable microbes (bacteria and fungi, as well as virus-like particles) when it reaches the islands (Griffin et al., 2001, 2003). Temporal and spatial variability of microbes
100
Figure 1. Satellite view of an African dust event reaching from Africa to the Caribbean and southeastern United States. This worldview image captured by NASA’s Earth-Probe TOMS satellite shows a large dust cloud stretching off the North African coast to cover much of the Caribbean and part of Florida. The TOMS aerosol index is a relative measure of absorbing aerosol particles suspended in the atmosphere. The higher the index (warmer colors), the greater the particle load. This image was taken June 23, 1998. The country of Mali is outlined in black.
within the dust clouds is significant (C.A. Kellogg and D.W. Griffin, unpublished data). DNA sequencing of bacterial and fungal isolates from air samples collected during a series of dust events passing over the United States Virgin Islands (USVI) has shown that approximately 25% are plant pathogens and 10% are opportunistic human pathogens (Griffin et al., 2001). Very little aeromicrobiology has been conducted in Africa. Three studies identified fungal species passively collected from the air in desert or dusty regions of Nigeria (Dransfield, 1966), Egypt (Ismail et al., 2002), and Sudan (Abdalla, 1988). To our knowledge, no studies have characterized airborne bacteria and fungi in northwest African regions that are traversed by, and contribute to, the large dust storms that cross the Atlantic. Here we identify microbes cultured from four dust events and one non-dust event in Bamako, Mali, West Africa.
2. Materials and methods 2.1. Air-sampling The TOMS aerosol index (Figure 1) was used to delineate dust and non-dust conditions. Air sam-
ples were collected using an in-house designed portable sampling system. The system consists of a vacuum pump attached to a PVC-pipe manifold, secured inside a carrying case. An additional 60 cm length of PVC-pipe is connected perpendicularly to this manifold, as a base for the filters. Presterilized polypropylene filter housings containing 47 mm diameter analytical test filters (cellulose nitrate membrane) with a pore size of 0.2 lm were obtained from Fisher Scientific (catalog #0974030G. Atlanta, GA). To take the air sample, the filters were removed from their sterile bags and placed on the analytical filter manifold. The lids were removed and a vacuum was applied using a vacuum pump; airflow rates through the filters were 10 l/min for 8–15 min per sampling. To control for handling contamination, an additional filter was removed from its bag, the filter placed on the manifold and allowed to sit without removing the lid. Both filters were then removed from the manifold, and the lids were sealed with Parafilm barrier film. The filters were returned to their original bags, which were sealed with tape, placed in Ziploc bags and mailed to the United States Geological Survey (USGS) microbiological laboratory in St Petersburg, Florida. Samples were processed immediately upon arrival, however, the
101 time from collection to processing ranged from 3 to 19 days, with an average of 14 days due to variable shipping times. In the lab, the filters were plated on R2A agar (Fisher Scientific, Atlanta, GA), a low nutrient medium preferred for culturing stressed microbes (Reasoner and Geldreich, 1985). We have compared R2A to standard fungal growth media (2% malt extract agar and Sauberaud–Dextrose agar) for these types of samples and found no difference in the number of fungi cultured (C.A. Kellogg, unpublished data). All analysis was conducted within a horizontal laminar airflow cabinet using sterile technique. Filters were halved using sterile scissors, and one half of each filter was placed on R2A agar, sample side up. The other half was refrigerated for later use in other experiments. Filters were incubated in the dark at 26 C for 48 h. Fungal and bacterial colonies were isolated from each other by isolation streaking onto fresh plates of R2A. Sixty bacteria and 8 fungi were picked from the February 3, 2001 dust sample; 9 bacteria and 9 fungi from March 2, 2001; 10 bacteria and 2 fungi from March 29, 2001; 9 bacteria and 1 fungus from April 5, 2001; and all 8 bacteria (zero fungi present on filter) from the non-dust air sample taken on March 1, 2002. All possible fungi were picked from each filter; bacteria were chosen based on different macroscopic colony morphologies. 2.2. Isolate identification For bacterial DNA extraction, bacterial isolates were touched with a sterile pipette tip, and the tip was then used to inoculate 180 ll of lysis buffer recommended for extraction of DNA from Gram positive bacteria in a DNeasy Tissue Kit (Qiagen Inc., Valencia, CA). The DNeasy Tissue Kit protocol was followed, and purified bacterial DNA was eluted in 100 ll of the kit elution buffer. Fungal DNA extraction was performed using the Mo Bio Ultraclean Soil DNA Isolation Kit (Mo Bio Laboratories, Inc., Solana Beach, CA). Approximately 25 mg of fungal tissue was placed into a 2.0 ml microcentrifuge tube containing garnet beads. The manufacturer’s alternative protocol for maximum yield was followed through step 6 (vortexing the tubes for 10 min). This step was followed by further bead beating in a FastPrep FP 120 (Bio101, Carlsbad, CA) for 30 s at a setting of 5.5. The Mo Bio protocol was then resumed at step
7 (centrifugation) and followed to the end. The purified fungal DNA was eluted in 50 ll of the kit elution buffer. Polymerase chain reaction (PCR) was used for 16S and 18S rDNA amplification using universal prokaryote and fungal primer sets [EF3 and EF4 for fungi] respectively (Shah and Romick, 1997; Smit et al., 1999). The PCR master mix recipe per reaction was: 10 ll of 10 · PCR buffer (Fisher Scientific, Atlanta, GA), 12 ll of 25 mM MgCl2 (Fisher Scientific, Atlanta, GA), 2 ll of 10 mM dNTP mix (Promega, Madison, WI), 0.5 ll of 5 units/ll Taq polymerase (Fisher Scientific, Atlanta, GA), 1 ll each of 10 nM upstream and downstream primers (synthesized by Operon Technologies, Inc. Alameda, CA), 5 ll of purified DNA eluate, and 69.0 ll of sterile H2O. The PCR amplification profile used for both 16S and 18S rDNA reactions was: one cycle for 2 min at 94 C, 40 cycles of [30 s at 94 C, 30 s at 45 C, 2 minutes at 72 C], one cycle of 10 min at 72 C and hold at 4 C. After PCR, each amplicon was then either sent off for direct sequencing by Northwoods DNA, Inc, (Becida, MN) or cloned into a plasmid vector using a TOPO TA Cloning Kit (Invitrogen Corp., Carlsbad, CA). Plasmid inserts (PCR amplicon) were sequenced by the University of Florida DNA Sequencing Core Laboratory (Gainesville, FL). GenBank Blast search (http:// www.ncbi.nlm.nih.gov/BLAST/) was used for amplicon/isolate identification. A few bacterial isolates that had GenBank matches to undescribed or uncultured organisms were submitted to Microbial ID (Newark, DE) for fatty acid analysis. Fungal isolates were also identified to the genus level using microscopy and an illustrated guide (St-Germain and Summerbell, 1996). 2.3. Antibiotic profiles Individual bacterial isolates were retrieved from frozen culture and streaked onto Tryptic Soy Agar (TSA – Fisher Scientific, Atlanta, GA) and allowed to grow for 48 h at 26 C. Standard protocols for the Kirby–Bauer method (Bauer et al., 1966) were utilized: cells were diluted to 0.5 McFarland standard using BBL Prompt Inoculation System (Bectin Dickinson, Franklin Lakes, NJ), then spread onto large (150 · 5 mm) Mueller– Hinton agar (Fisher Scientific, Atlanta, GA) plates with sterile cotton-tipped swabs to obtain an even distribution of cells. A 12-Place BBL Sensi-Disc
102 Self-Tamping Designer Dispenser System (Bectin Dickinson, Franklin Lakes, NJ) was used to dispense 10 antibiotic-impregnated discs (BBL SensiDisc, Bectin Dickinson, Franklin Lakes, NJ) onto each plate, and then the plates were incubated at 26 C overnight. Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922) were used as standard controls, and those plates were incubated at 37 C overnight. Zones of inhibition were measured in millimeters and recorded after 18–20 h. The Kirby–Bauer method is meant for use in clinical isolates and may not be interpretable the same way for environmental isolates. With this in mind, we used the resistant/susceptible range for Staphylococcus aureus to classify all the Gram positive isolates. The only Gram negatives tested were the Acinetobacters, which had a listed range. Any measurements that fell into an ‘intermediate’ area were coded as susceptible, marking as resistant only those isolates that were well under the minimum measurement for that classification. Concentrations of antibiotics in discs: Penicillin G – 10 lg, Gentamicin – 10 lg, Cefataxime – 30 lg, Ciprofloxacin – 5 lg, Erythromycin – 15 lg, Chloramphenicol – 30 lg, Tetracycline – 30 lg, Ampicillin – 10 lg, Nitrofurentoin – 300 lg, Oxacillin – 1 lg. 2.4. Accession numbers These sequence data have been submitted to the GenBank database under accession numbers AY211095 (Mali 1) to AY211189 (Mali 345) for the bacterial isolates, and AY227757 (Mali 65) to AY227770 (Mali 224) for the fungal isolates.
3. Results and discussion Air samples were taken during dust and non-dust events from a roof-top in Bamako, Mali, using a sterile filtration system. These filters were sent to the USGS laboratory in St Petersburg, FL, and half of each filter was cultured for viable microbes on R2A agar medium. A wide variety of bacteria and a few fungi were visible on the filters after a 48-h incubation. Many of the bacterial colonies were highly pigmented (colors ranging from clear to dark yellow, orange, and pink), which may be a survival mechanism to protect against UV-radiation while airborne, or an effect of the culture
medium. During dust events the number of bacteria detected in these samples ranged from 720 to 15,700 colony-forming units per cubic meter. Fungal counts were considerably lower, ranging from 80 to 370 CFU/m3. Samples taken during non-dust events (background) had 200–1100 bacterial CFU/m3 and 0–130 fungal CFU/m3. Our sampling site was located within an urban area, and this relatively high background concentration of viable organisms may be due to resuspension of dust by local traffic or wind. Also, some microbes may remain suspended in the air after a dust event has passed, until a rare rain event scrubs the air. Thus, we feel that non-dust event microbes are also of interest, as they likely reflect previous dust events in this area. With the exception of a single event (720 CFU/m3, during the May 2001 dust event), all of the Mali bacterial concentrations are one to two orders of magnitude higher than those found in the Virgin Islands during dust events (Griffin et al., 2001, 2003), and are two to three orders of magnitude higher than those measured in Barbados (J.M. Prospero, E. Blades, G. Mathison, and R. Naidu, submitted). Our fungal counts are roughly equivalent to those detected in the Virgin Islands during dust events, which are about an order of magnitude higher than what has been reported from Barbados. The ranges of colony-forming units per cubic meter listed here are certainly minimum estimates. It is important to note that only ca. 1% of the total bacterial community will grow on any given medium (Torsvik et al., 1990), so while culturing proves that the microbes are viable, it also restricts the number and composition that are detected. Filter-based methods of aerosol collection may dessicate bacteria, although we have endeavored to minimize this problem by sampling at a low flow rate for a very short period of time (8– 15 min). In addition, the unavoidable extended shipping period may also have biased the samples toward hardier strains. This methodology was employed because of the remote sampling location (viable impaction or liquid impinger methods would have required sample processing in Africa, which would have been cost and time prohibitive). We acknowledge that these sources of stress may have preferentially selected for spore-forming and dessication-resistant strains in these samples, leading to an under-representation of vegetative and dessication-sensitive strains. However, we
103 point out that spore-forming and dessicationresistant organisms are those most likely to survive long-distance transport in the dust, and are therefore of special interest. Previous studies of African dust air samples, taken in the Caribbean, were also conducted using filter-based systems, sampling for periods of 20 min (Griffin et al., 2001, 2003) or 24 h (J.M. Prospero, E. Blades, G. Mathison, and R. Naidu, submitted). From four dust events and one non-dust sample, we have identified 94 bacterial isolates and 20 fungal isolates by 16S and 18S DNA sequencing, respectively (Tables 1 and 2). Note that the microbes identified are a subset of the total viable organisms detected, not a complete catalog. The majority of the bacteria identified were found to be Gram positive (96%), and many are spore-formers. The 19 bacterial genera represented in our samples contain individuals typically found in soil, the marine environment, and on human skin. Bacillus sp., which are prevalent in soil and capable of forming spores to survive aerial transport, constitute 38% of the bacterial isolates identified. This result is consistent with the Barbados microbial data in which most of the bacteria isolated were Bacillus sp. (J.M. Prospero, E. Blades, G. Mathison, and R. Naidu, submitted). Another frequently isolated genus is Kocuria, particularly one strain of K. erythromyxa (now K. rosea) (Rainey et al., 1997; Schumann et al., 1999). An isolate of this species obtained from a dust sample taken in the Virgin Islands (Griffin et al., 2001) is 100% identical (737 bp, no gaps) to one of the isolates we obtained from dust in Mali. This strain of K. rosea appears to be fairly cosmopolitan, but since little microbial biogeography has been conducted, it is hard to say how significant it is to find identical isolates in locations roughly 5000 km apart. Nineteen bacterial isolates from Virgin Island air samples (Griffin et al., 2001) shared genus and species with the Mali isolates. Pair wise comparison between the Caribbean and African sequences revealed that, other than the Kocuria 100% match discussed above, only one other bacterium had close similarity; a Bacillus pumilus from the Virgin Islands had a single base pair difference from its Mali counterpart, making them 99% identical (528/529 bp, no gaps). It should be noted that the Mali filters had so much microbial growth that only a subset of the bacteria were identified for any given filter. As a result, there may be more isolates
in common between the African samples and Caribbean samples, but they were not among the randomly chosen isolates picked for identification. Several of the bacteria cultured from the African dust are species that were originally identified in the Antarctic from marine sea ice brine or ponds (Kocuria polaris, Planococcus mcmeekinii, Planococcus sp. ‘SOS Orange’, (Junge et al., 1998; Sheridan and Brenchley, 2000; Reddy et al., 2003). It has been hypothesized that during past glacial periods, changes of the Hadley circulation allowed dust from tropical deserts, including the Sahara, to be transported to the polar regions instead of to the tropical ocean (Chylek et al., 2001). A more likely scenario for these geographically distant but closely related (97–99% similarity) organisms is that they belong to cosmopolitan species that are capable of surviving in a variety of climates. While there is evidence of a few bacterial species that can survive only at the Earth’s poles, the majority of bacteria seem to be widely distributed and adaptable (Staley and Gosink, 1999). Of the 94 bacteria characterized from the Mali air samples, 10% are animal pathogens, 5% are plant pathogens, and 27% are opportunistic human pathogens (Table 1). In contrast, the Virgin Islands samples contained 25% plant pathogens and only 10% opportunistic human pathogens, including the fungi (Griffin et al., 2001). Some of the pathogens are particularly interesting. Acinetobacter calcoaceticus has been linked to bovine spongiform encephalopathy (BSE), aka ‘Mad Cow Disease’ (Tiwana et al., 1999). One of the Kocuria species we isolated was most similar to a bacterium that had been found in advanced noma lesions in Nigerian children (Paster et al., 2002). As these wounds are open to the environment, it is logical that this soil bacterium becomes a part of the infectious mix in noma lesions. Staphylococcus xylosus has been found to be the causative agent for septicemia in a loggerhead sea turtle (Caretta caretta) off the Canary Islands in 1999 (Torrent et al., 2000). Located off the coast of northern Africa, the Canary Islands are within the loggerheads’ migration route, and African dust blankets the Canary Islands frequently. Only three genera of viable fungi were detected in the Mali dust samples: Cladosporium, Aspergillus, and Alternaria (Table 2). All three fungal genera detected are considered cosmopolitan soil fungi (St-Germain and Summerbell, 1996). Cladosporium
104 Table 1. Bacterial isolates identified from air samples taken in Bamako, Mali, West Africa Most similar genus/species (GenBank)
Accession #
Isolatesa
Similarity score
Pathogen?b
Acinetobacter calcoaceticus
X81668
Mali 40 Mali 42
646/653 (98%) 713/715 (99%)
A, H A, H
Acintobacter sp. phenon 2
AJ278311
Mali 41
685/691 (99%)
Agrococcus jenensis
X92492
Mali 157
644/651 (98%)
Arthrobacter nicotianae
X80739
Mali 31
737/749 (98%)
Arthobacter protophormiae
X80745
Mali 36
720/731 (98%)
Bacillus aminovorans NCIMB 8292
X62178
Mali Mali Mali Mali Mali Mali Mali
574/609 719/732 527/565 660/671 746/759 733/766 740/751
Bacillus sp. AS-38
AJ391199
Mali 14
623/636 (97%)
Bacillus endophyticus
AF295302
Mali 49
725/726 (99%)
Bacillus flexus
AB021185
Mali 21
697/732 (95%)
Bacillus firmus
X60616
Mali 228
690/703 (98%)
Bacillus kangii
AF281158
Mali 20
695/706 (98%)
Bacillus sp. LMG 20241
AJ316313
Mali 342
510/513 (99%)
Bacillus megaterium
AF142677
Mali 59
755/757 (99%)
Bacillus sp. MR-4
AF264685
Mali 10
605/621 (97%)
Bacillus mycoides strain 10206
AF155957
Mali 46
662/664 (99%)
Bacillus sp. N6
AB043854
Mali 51
760/786 (96%)
Bacillus niacini
AB021194
Mali Mali Mali Mali
715/733 803/804 695/696 628/629
Bacillus pumilus
AB048252
Mali 34 Mali 38
706/721 (97%) 668/669 (99%)
P, H P, H
Bacillus pumilus KL-052
AY030327
Mali 340
529/529 ð100%Þ
P, H
Bacillus sp. S10
AJ242775
Mali 13
680/686 (99%)
Bacillus subtilis
Z99104
Mali 52
736/736 (100%)
H
Bacillus subtilis
AJ276351
Mali 145
629/629 (100%)
H
Bacillus subtilis
AB065370
Mali 338
582/585 ð99%Þ
H
AJ252574
708/727 (97%) 739/760 (97%) 657/661 (99%)
H
AF221062
Mali 44 Mali 45 Mali47
Bacillus sp. 19495
AJ315063
Mali 135
581/606 (95%)
Bacillus sp. 82344
AF227848
Mali 223
650/654 (99%)
Mali 230
546/549 (99%)
Soil bacterium SI-4 (Bacillus subtilis by fatty acid ID) Bacillus sp. YKJ-11
(cereus/anthracis/thuringiensis)
12 37 48 53 57 58 60
43 54 104 148
(94%) (98%) (93%) (98%) (98%) (95%) (98%)
P, H
A, P, H
(97%) (99%) (99%) (99%)
H
105 Table 1. (Continued) Most similar genus/species (GenBank)
Accession #
Isolatesa
Similarity score
Bacillus sp. 86348
AF227850
Mali 30
738/752 (98%)
Blackwater bioreactor bacterium BW7
AF394172
Mali 244
418/434 (96%)
Corynebacterium sp.
X89005
Mali 15 Mali 24 Mali 33
729/735 (99%) 713/723 (98%) 718/728 (98%)
A, H A, H A, H
Corynebacterium cf. aquaticum
AJ244681
Mali 339
541/551 (98%)
A, H
Dietzia sp. JTS6048-306
AB010904
Mali 88-02 Mali 159-02
699/701 (99%) 582/584 (99%)
H H
Gordonia terrae
X92482
Mali 56
690/690 (100%)
H
Gram Positive Bacterium Wuba45 (Deinococcus erythromyxa by fatty acid ID)
AF336354
Mali 18
493/500 (98%)
Kocuria erythromyxa (rosea)
Y11330
Mali Mali Mali Mali Mali Mali Mali Mali Mali
718/722 730/733 645/665 622/640 641/650 576/577 646/663 513/529 629/644
Kocuria rosea
X87756
Mali 11
711/717 (99%)
Kocuria polaris
AJ278868
Mali 345
724/728 (99%)
Kocuria sp. oral clone AW006
AF385532
Mali 249
656/681 (96%)
Microbacterium barkeri
X77446
Mali 50
676/694 (97%)
Micrococcus sp.
AF218240
Mali 26 Mali 29 Mali 39
597/601 (99%) 709/713 (99%) 764/766 (99%)
Micrococcus luteus
AJ409096
Mali 28
634/654 (96%)
Micrococcus sp. SMCC ZAT351
AF196342
Mali 2 Mali 35
745/769 (96%) 695/717 (96%)
Paenibacillus 5D2
AF245034
Mali 55
535/578 (92%)
H
Paenibacillus illinoisensis
D85397
Mali 9
695/703 (98%)
H
Paracoccus sp. MBIC3345
AB012914
Mali 27
704/715 (98%)
H
Planococcus sp. JG07 (Planomicrobium koreense gen. nov. sp. nov.)
AF144750
Mali 3 Mali 5
655/671 (97%) 660/672 (98%)
Planococcus mcmeekinii (Planomicrobium mcmeekinii)
AF041791
Mali 8
743/748 (99%)
Planococcus sp. ‘SOS Orange’
AF242541
Mali 1
708/724 (97%)
6 22 32 139 156 173 234 343 344
Pathogen?b
(99%) (99%) (96%) (97%) (98%) (99%) (97%) (96%) (97%)
H
106 Table 1. (Continued) Most similar genus/species (GenBank)
Accession #
Isolatesa
Similarity score
Mali Mali Mali Mali
661/677 661/676 663/678 624/636
4 16 17 167
Pathogen?b
(97%) (97%) (97%) (98%)
Rhodococcus ruber
X80625
Mali 25
727/727 (100%)
Saccharococcus sp. (uncultured)
AJ306648
Mali Mali Mali Mali Mali Mali Mali
591/625 627/662 624/659 622/657 657/693 536/570 560/594
Staphylococcus gallinarum (ATCC35539T)
D83366
Mali 94
676/677 (99%)
A, H
Staphylococcus xylosus
D83374
Mali 7
713/716 (99%)
A
Streptomyces sp. CHR28
AF026081
Mali 226
670/672 (99%)
Uncultured bacterium #0319-6J10 (unknown Bacillus sp. by fatty acid ID)
AF234076
Mali 19
557/590 (94%)
Uncultured hydrocarbon seep bacterium BPC090 (Aureobacterium liquefaciens by fatty acid ID)
AF154098
Mali 23
613/622 (98%)
Zoogloea ramigera
X74914
Mali 147-01
627/646 (97%)
90-02 93 103-01 124 175 227 235
(94%) (94%) (94%) (94%) (94%) (94%) (94%)
H
a
Mali 1 to 60 are from February 3, 2001 (dust event); Mali 88-02 to 139 are from March 2, 2001 (dust event); Mali 145 to 175 are from March 29, 2001 (dust event); Mali 223 to 249 are from April 5, 2001 (dust event); Mali 338 to 345 (italics) are from March 1, 2002 (nondust event). b Species that are known to be pathogenic to animals (A), plants (P) or are opportunistic pathogens of humans (H).
sp. are generally non-pathogenic, but the other two genera contain species capable of causing skin and pulmonary infections in immunocompromised hosts (St-Germain and Summerbell, 1996). These fungi have all been detected in the air in the Western Desert of Egypt, with Aspergillus sp. and Alternaria sp. being the dominant fungi in that region (Ismail et al., 2002). All the Cladosporium sp. isolated from Mali air samples that were identified by sequencing were identical to each other. Cladosporium sp. have been found in both dust and non-dust air samples in the Virgin Islands, but none of the other genera were observed (Griffin et al., 2001). Genetic comparison of the four Cladosporium cladosporioides identified in the Virgin Islands (Griffin et al., 2001) to a representative Mali isolate (Mali 176) show similarities of 99–100%, with 0–2 gaps for more than 650 bp.
The transcontinental movement of pathogens in African dust has potentially significant implications for downwind ecosystems, including effects on environmental health (e.g. coral reefs), agriculture and livestock, and human health. Peaks in the airborne dust record, measured in Barbados over the past 30 years, correspond to some of the major coral morbidity/mortality events in the Caribbean (Shinn et al., 2000). It has recently been determined that a terrestrial fungus, Aspergillus sydowii, is the cause of disease in Caribbean sea fans (Smith et al., 1996); and the infectious form of this fungus has been identified in air samples collected during African dust events in the Virgin Islands (Weir et al., 2000). Intercontinental dispersal of plant pathogens has long been recognized and is of particular concern because of the limited genetic diversity of many contemporary food
107 Table 2. Fungi isolated from African dust events in Mali, Africa Most similar genus/species (GenBank) NDc ND ND Cladosporium cladosporioides ND Cladosporium cladosporioides ND Cladosporium cladosporioides Cladosporium cladosporioides Cladosporium cladosporioides ND Cladosporium cladosporioides Aspergillus niger Cladosporium cladosporioides Alternaria sp. Aspegillus sp. Aspergillus versicolor Cladosporium cladosporioides Aspergillus niger Aspergillus versicolor
Accession #a
U20381 U20381 U20381 U20381 U20381 U20381 D63697 U20381 U05199, U05197, U05194 AF516140, AY083218, M55626 AB002064 U20381 D63697 AB002064
Microscopic ID (Genera)
Isolatesb
Similarity score
Cladosporium Cladosporium Cladosporium Cladosporium Cladosporium Cladosporium Cladosporium Cladosporium Cladosporium Cladosporium Cladosporium Cladosporium Aspergillus Cladosporium Alternaria
Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali
ND ND ND 756/757 ND 673/673 ND 768/769 768/769 736/736 ND 768/769 502/507 764/765 740/740
Aspergillus
Mali 79
620/620 (100%)
Aspergillus Cladosporium Aspergillus Aspergillus
Mali Mali Mali Mali
749/751 768/769 727/736 727/728
62 63 64 65 66 67 68 69 71 72 73 74 75 76 77
80 176 177 224
(99%) (100%) (99%) (99%) (100%) (99%) (99%) (99%) (100%)
(99%) (99%) (98%) (99%)
a
In cases where the sequence matched more than one species within the genera equally well, and microscopy did not clarify the species, the top three GenBank matches are listed. b Isolates 62–69 are from February 3, 2001; 71–80 are from March 2, 2001; 176–177 are from March 29, 2001; 224 is from April 5, 2001. c ND = not determined. All isolates were identified to the genus level by microscopy; several representative isolates of each type from each date were also analyzed by 18S DNA sequence analysis for confirmation. The fungal 18S DNA fragments often come back from a Blast search with multiple matches that are equally good, so narrowing the genera by microscopy was essential to correct identification.
crops (Brown and Hovmøller, 2002). Human health may also be adversely affected by inhalation of viable microorganisms. Exposure to airborne microbes and biologically derived particulate matter can trigger allergic responses in humans. In addition to the risk associated with exposure to airborne pathogens, exposure-response studies have shown that individuals exposed to nonpathogenic airborne microbes are at a higher risk of developing symptoms of disease than those who are not exposed (Eduard et al., 2001). The Caribbean, where desert dust activity is common, has some of the world’s highest recorded incidence rates (18–23%) of asthma (Howitt, 2000). Eleven antibiotics, including some of the most commonly used antibiotics in Mali (Koumare and Bougoudogo, 1993), were used to further characterize forty-seven of the bacteria by their antibiotic susceptibilities (Table 3). Resistance to the antibi-
otics nitrofurantoin and oxacillin was the most noticeable trend among the Mali bacterial isolates (43% and 30%, respectively). Approximately onefifth of the bacteria (19%) were resistant to chloramphenicol. In a 1980–1991 study of over 2000 clinical bacterial isolates from Mali, 57% of the Staphylococcus aureus were resistant to oxacillin, and over 50% of the Escherichia coli were resistant to chloramphenicol (Koumare and Bougoudogo, 1993). Overall the researchers concluded that the level of resistance in clinical bacteria had not changed over the decade for most antibiotics, but was increasing markedly for oxacillin. Nearly all the clinical isolates in that study showed strong resistance to ampicillin and tetracycline, a trend we did not observe in our environmental isolates. An earlier study found that in testing clinical isolates obtained in Mali, imipenem was more active against staphylococci and streptococci and many
Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali
Isolate
1 2 4 5 6 7 8 9 10 11 12 13 15 17 18 19 21 23 24 25 26 29 30 31 32 33 34 35 36 37 39 40 41 42 44 46
Planococcus Micrococcus Planococcus Planococcus Kocuria Staphylococcus Planococcus Paenibacillus Bacillus Kocuria Bacillus Bacillus Corynebacterium Planococcus Deinococcus Bacillus Bacillus Aureobacterium Corynebacterium Rhodococcus Micrococcus Micrococcus Bacillus Arthrobacter Kocuria Corynebacterium Bacillus Micrococcus Arthrobacter Bacillus Micrococcus Acinetobacter Acinetobacter Acinetobacter Bacillus Bacillus
Genus
30 36 26 38 22 27 22 23 30 35 42 37 30 39 44 22 24 24 36 33 39 31 28 35 28 28 42 33 35 41 40 17 19 17 32 23
Penicillin G
18 15 19 29 14 32 21 27 35 25 28 30 28 22 25 13 32 30 29 0 20 22 32 27 22 22 34 25 20 30 27 27 25 23 34 25
Gentamicin
Zone of inhibition (mm)
Table 3. Antibiotic susceptibilities of bacterial African dust isolates
22 24 15 39 25 24 24 0 20 34 35 22 30 41 40 26 32 35 35 35 28 33 23 35 33 29 20 43 30 37 30 24 22 22 27 20
Cefataxime 13 27 22 32 19 27 21 17 29 16 35 35 25 33 25 22 22 22 30 15 20 21 26 18 25 24 32 27 19 33 22 28 27 26 35 28
Ciprofloxacin 24 15 0 8 18 30 12 30 32 27 33 34 21 36 25 20 32 24 25 25 24 27 31 27 25 25 29 36 27 31 26 20 21 18 37 31
Erythromycin 0 13 8 25 14 28 10 28 30 26 30 32 23 9 28 21 29 34 24 30 11 24 35 36 22 8 20 25 7 30 35 28 26 0 38 31
Chloramphenicol 32 18 18 30 25 31 20 35 35 23 32 31 25 28 19 20 33 32 28 30 30 30 31 29 31 10 31 32 10 30 35 25 30 22 34 25
Tetracycline 31 40 31 49 21 28 26 20 34 37 47 46 31 41 39 23 29 23 33 29 41 31 NDa 33 46 35 41 36 37 52 37 25 24 25 34 25
Ampicillin
14 6 0 27 0 18 18 25 32 0 22 31 11 25 8 0 20 26 9 15 10 10 30 9 0 9 24 0 11 20 12 11 10 10 22 17
Nitrofurentoin 0 27 7 25 18 12 11 0 16 25 27 20 7 25 26 8 0 15 8 12 0 0 26 19 31 0 21 30 28 34 0 NAb NA NA 20 15
Oxacillin
108
109
34 32 12 22 35 36 35 34 32 26 33
29 35 35 30 32 31 34 31 35 30 35
32 34 32 30 33 40 32 29 31 36 35
50 52 30 18 37 35 58 31 33 16 43
31 20 21 0 28 27 25 29 20 21 23
33 36 9 0 11 19 30 28 28 12 20
enteric bacteria than most third generation cephalosporines (Koumare et al., 1991). We originally included imipenem in our antibiotic resistance study for this reason, but found all the environmental bacteria we tested to be highly sensitive to the drug, often to the point of the areas of inhibition being too large to be accurately measured (data not shown). Much remains to be learned about the microbial content of African desert dust. The microbial communities being transported by dust storms have the potential to affect ecosystems and public health, both proximally and half a world away. Culture techniques confirm that microbes in the airborne dust are viable, but only reveal the small percentage of organisms that will grow on a given medium. Many fastidious bacteria and fungi, as well as all the viruses, cannot be detected by this method. The next step is to use direct DNA extraction techniques to access the rest of the microbes present in African dust events.
White cells indicate susceptiblity; shaded cells indicate resistance. a ND = not defined, unable to measure. b NA = not applicable to that type of bacterium.
Bacillus Bacillus Bacillus Microbacterium Bacillus Bacillus Bacillus Bacillus Bacillus Saccharococcus Bacillus 47 48 49 50 51 52 53 54 59 124 135 Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali Mali
Table 3. (Continued)
44 50 25 15 44 38 48 22 35 30 40
ND 30 34 11 26 35 24 21 30 30 30
34 38 25 30 35 30 43 34 38 37 33
26 33 33 23 27 35 35 29 30 25 33
Acknowledgements We gratefully acknowledge the support of NASA Goddard Space Flight Center’s Earth Science and Public Health Program. C.A.K. was also supported by a Mendenhall Fellowship from the USGS. We thank M. Ranneberger, B. Eyrich of the Ecole Americane for their help in obtaining samples. We thank Jay R. Herman of NASA for the TOMS image used in Figure 1.
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